KEYNOTE TALKS (UTC+1)
| Keynote talk 2 (virtual) | Saturday 16.12.2023 | 08:40 - 09:30 | Room: 001 (Building H) |
| Network extraction and modelling | |||
| Speaker: M. Billio | Chair: Christina Erlwein-Sayer | ||
| Keynote talk 1 | Saturday 16.12.2023 | 08:40 - 09:30 | Room: 001-002 (Building G) |
| Rage against the mean: An introduction to distributional regression | |||
| Speaker: T. Kneib | Chair: Armelle Guillou | ||
| Keynote talk 4 | Sunday 17.12.2023 | 18:20 - 19:10 | Room: 001 (Building H) |
| The risk management approach to macro-prudential policy | |||
| Speaker: S. Manganelli | Chair: Alessandra Amendola | ||
| Keynote talk 3 | Sunday 17.12.2023 | 18:20 - 19:10 | Room: 001-002 (Building G) |
| AI for the acceleration of scientific discovery | |||
| Speaker: C. Bekas | Chair: Erricos Kontoghiorghes | ||
| Keynote talk 5 | Monday 18.12.2023 | 17:30 - 18:20 | Room: 001-002 (Building G) |
| Vine copula-based regression models | |||
| Speaker: C. Czado | Chair: Ana Colubi | ||
PARALLEL SESSIONS (UTC+1)
| Parallel session C: CMStatistics | Saturday 16.12.2023 | 10:00 - 12:05 |
| B0412: C. Montorsi | |
| Predicting depression in old age: combining life course data with machine learning | |
| B0685: F. Schirripa Spagnolo, S. Marchetti, C. Giusti, M. Pratesi, G. Bertarelli, L. Biggeri | |
| Small area estimation of monetary poverty indicators with poverty lines adjusted using local price indexes | |
| B0696: M. Ciommi, C. Gigliarano, F. Mariani, G. Polinesi | |
| Assessing multidimensional poverty of the Italian provinces during COVID-19: A small area estimation approach | |
| B0697: F. Crescenzi, A. Nigri, G. Betti | |
| Measuring the poverty-free life expectancy: A temporal analysis on EU-SILC data | |
| B0762: A. Sanchez, E. Jimenez-Fernandez | |
| Unsupervised machine learning for estimating the socioeconomic vulnerability in the European Union |
| Session EO396 | Room: 262 |
| Time series: Detecting change-points and dependence | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Herold Dehling | Organizer: Herold Dehling |
| B0416: M. Wendler | |
| Dependent wild bootstrap for change-point detection in functional time series and random fields | |
| B0892: D. Vogel, H. Dehling, M. Wendler | |
| First versus full or first versus last: U-statistic change-point tests under fixed and local alternatives | |
| B0938: K. Vuk, H. Dehling, M. Wendler | |
| Detecting early or late change-points in time series using U-statistics | |
| B1215: M. Kroll, A. Betken, H. Dehling | |
| Testing independence of mixing time series using the distance covariance | |
| B1461: A. Betken, H. Dehling | |
| Testing for independence of long-range dependent time series based on distance correlation |
| Session EO046 | Room: 335 |
| Copulas and dependence modelling | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Piotr Jaworski | Organizer: Piotr Jaworski |
| B0303: M. Manstavicius | |
| Generalizations of Kendall's tau: Meaning and constructions | |
| B0315: P. Jaworski | |
| On certain notion of tail dependence of copulas | |
| B0348: O. Sahin, H. Joe | |
| Vine copula based classifiers | |
| B0546: C. Genest | |
| Orthogonal decomposition of probability densities in Bayes spaces | |
| B1024: J. Neslehova, S. Perreault, T. Duchesne | |
| Hypothesis tests for structured rank correlation matrices |
| Session EO237 | Room: 340 |
| Analysis of spatial patterns in neuroimaging | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Sarah Weinstein | Organizer: Sarah Weinstein |
| B0176: J.Y. Park, R. Zhang | |
| Mitigating inter-scanner biases in high-dimensional neuroimaging data via spatial Gaussian process | |
| B0538: A. Chen | |
| Structure-function gradients along the brain cortex | |
| B0738: C. Chen, M. Tisdall, D. Wolk, S. Das, P. Yushkevich, R. Shinohara | |
| Subject-level weights for detecting brain volume differences | |
| B0866: M. Lindquist | |
| Individualized spatial topography in functional neuroimaging | |
| B0889: D. Tudorascu | |
| Challenges in data harmonization for Positron emission tomography (PET) imaging studies of Alzheimer's disease |
| Session EO105 | Room: 348 |
| Statistical network analysis: Theory, methods, and applications | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Joshua Cape | Organizer: Joshua Cape |
| B0464: M. Schaub | |
| Learning from networks with unobserved edges | |
| B0558: D. Ghoshdastidar, M. Sabanayagam, P. Esser | |
| Analyzing graph neural network architectures through the neural tangent kernel | |
| B0656: C. Fritz, M. Schweinberger, D. Hunter | |
| A statistical platform for discrete and dependent attribute and network data generalizing GLMs | |
| B0868: F. Sanna Passino | |
| Bayesian nonparametric projected normal mixture models for spectral graph clustering with degree heterogeneity | |
| B0951: A. Kreiss, E. Mammen, W. Polonik | |
| Using Hawkes processes to model sparse event networks |
| Session EO438 | Room: 350 |
| Advances in statistical boosting | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Colin Griesbach | Organizer: Colin Griesbach |
| B0641: L. Knieper, E. Bergherr, T. Hothorn, N. Mueller-Voggel, C. Griesbach | |
| A novel gradient boosting framework for generalized additive mixed models | |
| B0906: T. Hepp, E. Bergherr | |
| Boosting mixtures of distributional regression models | |
| B0937: E. Bergherr, T. Hepp, M. Balzer, S. Hutter | |
| Gradient boosting for Dirichlet regression: Impact of protests on election results | |
| B1016: A. Daub, A. Mayr, B. Zhang, E. Bergherr | |
| Gradient boosting for GAMLSS using adaptive step lengths | |
| B1643: J. Cavieres | |
| Bayesian semiparametric spatial model using template model builder (TMB) |
| Session EO525 | Room: 351 |
| Advances in statistical imaging | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Michele Guindani | Organizer: Michele Guindani |
| B1078: A. Gibberd, T.-S. Chan, X. Tian, K. Zheng | |
| Exploring dynamic factors of fMRI activity in the presence of sparse loadings | |
| B1109: D. Telesca | |
| Covariate-adjusted mixed membership models for functional data | |
| B1331: J. Kornak | |
| Modeling longitudinal trajectories of neuropsychological and neuroimaging brain changes | |
| B1336: R. Guhaniyogi, A. Scheffler, R. Gutierrez | |
| Bayesian learning of heterogeneous image sources: A journey through non-parametric models to deep learning architecture | |
| B1517: R. Mena | |
| Bayesian shape analysis via the projected normal distribution |
| Session EO296 | Room: 353 |
| Statistical methods for biological and medical applications | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Alberto Cassese | Organizer: Alberto Cassese |
| B0475: P. Belloni | |
| Improving adverse drug event prediction using biochemical features extracted with ChemBERTa | |
| B0517: T.Q. Asenso, M. Zucknick | |
| Accounting for population heterogeneity by modeling interactions with the pliable lasso | |
| B0902: V. Ballerini | |
| Causal effects on time-to-event outcomes in an oncology RCT with treatment discontinuation | |
| B1005: F.J. Bargagli Stoffi | |
| Characterizing heterogeneity of causal effects in air pollution epidemiology via Bayesian causal inference | |
| B1015: E. Sabbioni, E. Bibbona, G. Mastrantonio, G. Sanguinetti | |
| Bayesian approach for modelling RNA velocity |
| Session EO083 | Room: 355 |
| Statistical learning in practice | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Alejandro Murua | Organizer: Alejandro Murua |
| B1013: X. Ju, H. Park, T. Tarpey | |
| Interpretable scalar-on-covariance regression with applications to functional connectivity | |
| B0527: S. Baran, M. Nagy-Lakatos | |
| Discrete post-processing of visibility ensemble forecasts using machine learning | |
| B1141: K. Dorman | |
| Learning CUT\&RUN peaks from replicate samples with high duplicate sampling and low signal | |
| B0332: A. Labbe, M. Lei, L. Sun | |
| BKTR - Bayesian kernelized tensor regression: Application to bike-sharing demand modeling | |
| B1128: R. Maitra, C. Llosa | |
| Fourier-structured tensor-variate distributions for high-resolution imaging applications |
| Session EO248 | Room: 356 |
| Design and analysis of experiments with modern applications | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Rakhi Singh | Organizer: Rakhi Singh |
| B0543: D. Woods | |
| Emulation of computer simulators with uncertain inputs | |
| B0379: W. Mueller, A. Pazman, M. Hainy | |
| A convex approach to optimum design of experiments with correlated observations | |
| B0465: J. Stufken, R. Singh | |
| TreeSS: A model-free Tree-based subdata selection method for prediction | |
| B0979: X. Deng, X. Cai, D. Lin, Y. Hong, L. Xu | |
| Adaptive-region sequential design with quantitative and qualitative factors in application to HPC configuration |
| Session EO434 | Room: 357 |
| Spatial and spatiotemporal peaks-over-threshold with flexible models I | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Thomas Opitz | Organizer: Thomas Opitz |
| B0243: P. Zhong, M. Brunner, T. Opitz, R. Huser | |
| Spatial modeling and future projection of extreme precipitation extents | |
| B0702: J. Richards, M. Sainsbury-Dale, A. Zammit Mangion, R. Huser | |
| Neural Bayes estimators for fast and efficient likelihood-free inference with spatial peaks-over-threshold models | |
| B1043: J. Koh | |
| Using spatial extreme-value theory with machine learning to understand compound extremes: A case study on heat | |
| B1224: P. Braunsteins, D. Bolin, S. Engelke, R. Huser | |
| The SPDE approach for spatial extremes | |
| B0976: C. Forster, M. Oesting | |
| Non-stationary models for extremal dependence |
| Session EO282 | Room: 401 |
| Branching and related processes I | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Miguel Gonzalez Velasco | Organizer: Ines M del Puerto, Miguel Gonzalez Velasco |
| B1760: M. Slavtchova-Bojkova, N. Yanev, O. Hyrien | |
| Multitype subcritical Markov branching processes with immigration generated by Poisson random measures | |
| B1828: I.M. del Puerto, M. Gonzalez Velasco, M. Molina, G. Yanev, N. Yanev | |
| Controlled branching processes subordinated by a renewal process | |
| B1572: A. Vidyashankar | |
| Bahadur-type asymptotics for estimates of ancestor mean of branching processes with immigration | |
| B1791: P. Martin-Chavez, M. Gonzalez Velasco, I.M. del Puerto | |
| Convergence of controlled branching processes to CBI-processes |
| Session EO127 | Room: 403 |
| Machine learning for environmental applications | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Tim Verdonck | Organizer: Tim Verdonck |
| B1704: S. Leyder, T. Verdonck, J. Raymaekers | |
| TSLiNGAM: DirectLiNGAM under heavy tails | |
| B1735: S. Mortier, T. Verdonck, T. De Schepper, S. Latre, B. Didrik Sigurdsson, R.P. Tchana Wandji, A. Hamedpour, B. Bussmann | |
| Inferring the relationship between soil temperature and normalized difference vegetation index with machine learning | |
| B1775: I. Janssens, T. Servotte, T. Verdonck | |
| Machine learning techniques for bio-accelerated mineral weathering | |
| B1793: T. Servotte, I. Janssens, T. Verdonck | |
| Optimal experiment design for environmental research using Bayesian optimization | |
| B1830: T. Decorte, S. Mortier, C. Suys, T. Verdonck | |
| Missing value imputation of sensor data for environmental monitoring |
| Session EO213 | Room: 404 |
| Non-stationary random fields, theory and applications | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Anastassia Baxevani | Organizer: Anastassia Baxevani |
| B0873: L. Llamazares, F. Lindgren, J. Latz | |
| Penalized complexity priors for stochastic partial differential equations | |
| B1487: K. Podgorski, J. Wallin, I. Rychlik | |
| Slepian models for moving averages driven by a non-Gaussian noise | |
| B1688: A. Baxevani, D. Hristopoulos, C. Andreou | |
| Effective probability distribution approximation for non stationary non Gaussian random fields | |
| B1749: A. Wylomanska | |
| Anomalous diffusion processes with random parameters | |
| B1265: A. Lenzi | |
| Towards black-box parameter estimation |
| Session EO241 | Room: 414 |
| Statistical methods for structural health monitoring | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Jan Gertheiss | Organizer: Jan Gertheiss |
| B1364: K. Maes, G. Lombaert | |
| The application of black-box modeling techniques to remove environmental influences on vibration monitoring data | |
| B0752: P. Wittenberg | |
| Covariate-adjusted sensor outputs for structural health monitoring: A functional data approach | |
| B0515: L. Neumann, P. Wittenberg, J. Gertheiss | |
| Confounder-adjusted covariances of sensor outputs and applications to structural health monitoring | |
| B0931: A. Mendler | |
| How to evaluate the probability of detection based on data from undamaged structures | |
| B1817: I. Okhrin, R. Jaekel, P. Baddam, M.R. Sanchez Figueroa | |
| Predicting bridge condition ratings |
| Session EO116 | Room: 424 |
| Recent cylindrical models and their related topics (virtual) | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Toshihiro Abe | Organizer: Toshihiro Abe |
| B0653: T. Abe, Y. Nakayama | |
| A simple heavy tailed cylindrical model and its applications | |
| B0907: Y. Miyata, T. Shiohama, T. Abe | |
| A hidden Markov model whose components are the Weibull-extended sine skewed von Mises distributions | |
| B1072: T. Shiohama, H. Ogata | |
| On some topics in complex-valued and circular time series modeling | |
| B1081: Y. Tsuruta | |
| Kernel-based nonparametric regression for cylindrical data | |
| B1089: T. Imoto | |
| New construction of cylindrical distributions |
| Session EO312 | Room: 442 |
| Recent developments in biostatistics | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Kathrin Moellenhoff | Organizer: Kathrin Moellenhoff |
| B0584: F. Kappenberg, J. Rahnenfuehrer | |
| AlertGS: Calculating alerts for gene sets based on individual dose-response modelling | |
| B0668: K. Schorning, K. Moellenhoff | |
| Optimal designs for identifying alert concentrations | |
| B0671: M. Lau, T. Schikowski, H. Schwender | |
| Statistical learning for constructing genetic risk scores | |
| B0682: N. Hagemann, G. Marra, F. Bretz, K. Moellenhoff | |
| Testing for similarity of multivariate mixed outcomes with application to efficacy-toxicity responses | |
| B1123: D. Dobler, M. de Gunst, M.T. Dietrich | |
| A general wild bootstrap scheme for counting process-based statistics with application to Fine-Gray models |
| Session EO186 | Room: 444 |
| Representation learning | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Marcell Tamas Kurbucz | Organizer: Marcell Tamas Kurbucz |
| B0253: N. Strodthoff | |
| Self-supervised learning for physiological time series data | |
| B0327: M.T. Kurbucz, A. Jakovac | |
| Pattern-based transformation for time series classification and anomaly detection | |
| B0367: T. Weber | |
| Exploring latent spaces: manipulating medical data through image editing | |
| B0434: G. Varando, H. Durand, M.-A. Fernandez-Torres, J. Munoz-Mari, M. Piles, G. Camps-Valls | |
| Learning causal representations with Granger rotated PCA | |
| B1126: M. Zulqarnain, W. Bajwa | |
| DiSK: An efficient algorithm for distributed and streaming $k$-PCA |
| Session EO270 | Room: 445 |
| Model assessment | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Maria Dolores Jimenez-Gamero | Organizer: Maria Dolores Jimenez-Gamero |
| B0297: D. Bagkavos, M. Guillen, J.P. Nielsen | |
| Robust and flexible model selection for multivariate local linear regression | |
| B0648: V. Alba-Fernandez, M.D. Jimenez-Gamero | |
| Simultaneous testing for proportions for a large number of populations | |
| B0744: E. Gonzalez-Estrada, A. Monter-Pozos | |
| Assessing the skew normality hypothesis using the Shapiro-Wilk test | |
| B0859: D. Gaigall, S. Wu, H. Liang | |
| A general approach for testing independence in Hilbert spaces | |
| B1599: E. Bothma, J. Allison, J. Visagie | |
| New classes of tests for the Weibull distribution using Stein's method in the presence of random right censoring |
| Session EO417 | Room: 446 |
| Causal inference | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Elizabeth Ogburn | Organizer: Elizabeth Ogburn |
| B1522: D. van Dyk, M. Autenrieth, D. Stenning, R. Trotta | |
| Stratified learning: A general-purpose statistical method for improved learning under covariate shift | |
| B1571: E. Ogburn | |
| Missing data with causal and statistical dependence | |
| B1737: A. Volfovsky | |
| A double machine learning approach to combining experimental and observational data | |
| B1917: J. Murray, A. Feller | |
| The weighting representation of Bayesian causal effect estimators |
| Session EO234 | Room: 447 |
| Statistical analysis of functional and complex data | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Alessia Pini | Organizer: Alessia Pini |
| B0843: D. Liebl, S. Otto, A. Kneip | |
| Combining concurrent and historical functional linear regression | |
| B1076: T. Bortolotti, R. Peli, G. Lanzano, S. Sgobba, A. Menafoglio | |
| A functional ground motion model for partially observed response profiles | |
| B1593: F. Vogel | |
| Examining quantiles of sensor outputs in structural health monitoring | |
| B0709: S. Vantini, J. Diquigiovanni, M. Fontana | |
| The importance of being a band: finite-sample exact conformal prediction bands for functional data | |
| B0858: A. Calissano, E. Maignant, X. Pennec | |
| Extending barycentric subspace analysis to a set of graphs |
| Session EO139 | Room: 457 |
| High-dimensional statistics | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Andreas Artemiou | Organizer: Andreas Artemiou, Sebastian Doehler |
| B0218: J. Virta, A. Artemiou | |
| Poisson PCA for matrix count data | |
| B1210: E. Solea | |
| Joint estimation of heterogeneous non-Gaussian functional graphical models with fully and partially observed curves | |
| B1225: S.J. Shin | |
| Variable selection in AUC-optimizing classification | |
| B1784: A. Reiner-Benaim, S. Doehler | |
| Identifying rare and weak effects in discrete count data from high throughput sequencing experiment | |
| B1806: S. Doehler, E. Roquain, I. Meah | |
| Online multiple testing with super uniformity reward |
| Session EO053 | Room: 458 |
| HiTEc: Clustering of complex data structures | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Maria Brigida Ferraro | Organizer: Maria Brigida Ferraro, Ana Belen Ramos-Guajardo |
| B0174: C. Biernacki | |
| Levels merging in the latent class model | |
| B0624: A.B. Ramos-Guajardo | |
| A clustering approach for random intervals based on an overlapping measure | |
| B1099: C. Di Nuzzo, D. Vicari | |
| A clustering model for asymmetric data: A within-cluster approach | |
| B0954: M. Sato-Ilic | |
| Principal component analysis for mixed high-dimension low-sample size data based on fuzzy-cluster scale | |
| B0518: A. Soubeiga, V. Antoine, A. Corteval, N. Kerckhove, S. Moreno, I. Falih | |
| Clustering and interpretation of time-series trajectories of chronic pain using evidential c-means |
| Session EO326 | Room: Virtual R01 |
| Tme series analysis for sustainable development goals | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Clara Cordeiro | Organizer: Clara Cordeiro |
| B1673: D. Prata Gomes, M. Neves | |
| The role of resampling methods in extreme value parameters estimation | |
| B1654: H. Mourino | |
| Sustainable development goals in marine biology: Using spectral analysis and cross-correlation to describe Chlorophyll-a | |
| B1678: M.R. Ramos, C. Cordeiro | |
| Trend methods in time series: Comparison and application within the 14th sustainable development goal | |
| B1680: A. Borges, C. Cordeiro, M.R. Ramos | |
| Analyzing sea level fluctuations and breakpoints: A statistical approach in support of sustainable development goal 14 | |
| B1657: C. Cordeiro, M. Neves, C. Coelho, S.V. Domingos | |
| Forecasting sea level rise: raising awareness about SDG14 |
| Session EC467 | Room: 352 |
| Bayesian statistics | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Pier Giovanni Bissiri | Organizer: CFE-CMStatistics |
| B0936: N.S. Upadhye, R. Chowdhury | |
| Hybrid method for constrained Bayesian optimization | |
| B1724: R. Yuasa, G. Kobayashi, S. Sugasawa, Y. Yamauchi | |
| Bayesian Tucker decomposition model with time varying factor matrices | |
| B1802: M. Maia Marques | |
| spBART: Adding smoothness for Bayesian additive regression trees through splines | |
| B0366: S. Jessup, M. Pigeon, M. Mailhot | |
| Uncertainty in heteroscedastic Bayesian model averaging | |
| B1726: F. Komaki, T. Sei | |
| Harmonicity of the right-invariant prior densities for group models with respect to the Fisher metric |
| Session EC470 | Room: 354 |
| Time-to-event analysis | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Andrej Srakar | Organizer: CFE-CMStatistics |
| B0489: P. Lambert | |
| Laplace approximations in double additive cure survival models with exogenous time-varying covariates | |
| B1434: T.P. Yuen, E. Musta | |
| Testing for sufficient follow-up in survival data with immunes | |
| B1626: A. Verhasselt, M. D Haen, I. Van Keilegom | |
| Copula based quantile modelling under dependent censoring | |
| B1587: O. Sercik, A. Verhasselt, S. Abrams | |
| Nonparametric estimation of the cross ratio function under right censoring | |
| B1538: M. Nugroho, S. Abrams, A. Verhasselt | |
| Nonparametric estimation of the cross-ratio function with splines |
| Session EC457 | Room: 455 |
| Statistical modelling | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Andriette Bekker | Organizer: CFE-CMStatistics |
| B1458: C. Ramsay, A. Krutto | |
| Calculating loss reserves for heavy-tailed insurance business | |
| B1510: S. Huckemann | |
| Modeling phylogenetic trees in the wald space | |
| B1596: D. Jayakumari, R. de Andrade Moral, J. Einbeck, J. Hinde | |
| A new distance-based framework based on half normal plots for count data | |
| B1674: S. Makgai, J. Ferreira, A. Bekker | |
| Statistical learning from data | |
| B0249: A. Guillou | |
| Estimation of marginal excess moments for Weibull-type distributions |
| Parallel session C: CFE | Saturday 16.12.2023 | 10:00 - 12:05 |
| Session CO154 | Room: 236 |
| New tests for financial time series models | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Jean-Michel Zakoian | Organizer: Christian Francq, Jean-Michel Zakoian |
| A0615: G. Sucarrat, O. Stauskas | |
| Testing the zero-process of intraday financial return for non-stationary periodicity | |
| A1083: C. Francq, J.-M. Zakoian, L. Trapani | |
| Detection of breaks in weak location time series models with quasi-Fisher scores | |
| A1080: J.-M. Zakoian, C. Francq | |
| Finite moments testing in a general class of nonlinear time series models | |
| A1922: J. Royer, R. Aumond | |
| Improving the robustness of Markov-switching dynamic factor models with time-varying volatility | |
| A1940: S. Telg, S. Fries, J.-M. Zakoian, J. van der Oord | |
| Fractional integration in mixed causal-noncausal models |
| Session CO037 | Room: 257 |
| Parameter uncertainty in portfolio selection and asset pricing | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Nathan Lassance | Organizer: Nathan Lassance |
| A0593: R.A. Schuessler, F. Nardari | |
| Ensembles of portfolio rules | |
| A1534: Y. Li, L. Chen, X. Zheng | |
| Estimating efficient frontier with all risky assets | |
| A0395: K. Saxena | |
| Calm your portfolio: the importance of disciplining intelligent but fickle forecasts in portfolio optimization | |
| A1756: L. Nechvatalova, J. Barunik | |
| Deep reinforcement learning and portfolio selection | |
| A0212: C. Torricelli, B. Bertelli | |
| ESG compliant optimal portfolios: optimizing after screening or screening while optimizing |
| Session CO235 | Room: 258 |
| Forecasting and climate econometrics | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Tommaso Proietti | Organizer: Tommaso Proietti, Robert Kunst |
| A0968: J. Gonzalo, L. Gadea | |
| Global and regional long-term climate forecasts: A heterogeneous future | |
| A1220: F. Marotta, H. Mumtaz | |
| Vulnerability to climate change: Evidence from a dynamic factor model | |
| A1568: T. Proietti | |
| Ups and drawdowns | |
| A0821: R. Kunst, M. Ertl, A. Wende | |
| Time-series evidence on the influence of the choice of seasonal adjustment method on forecasting accuracy | |
| A0922: I. Fortin, J. Hlouskova | |
| Does addressing uncertainty improve nowcasts of the Austrian economy? |
| Session CO165 | Room: 259 |
| Macro-financial risk | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Claudio Morana | Organizer: Claudio Morana |
| A0211: C. Morana | |
| Green risk in Europe | |
| A0216: M. Hartmann | |
| Structural determinants of house prices-at-risk | |
| A0230: A. Glas, C. Conrad, M. da Silva Rapp | |
| Who is updating stock market expectations in response to market turmoil? | |
| A0258: C. Ochsner, L. Other, L. Salzmann, T. Kroeger | |
| Time to invest? German economic growth prospects in the 21 century | |
| A1800: M. Karanasos | |
| Hessenbergians over a matrix ring: Analyzing VARMA models with variable coefficient matrices |
| Session CO398 | Room: 261 |
| Advances in forecasting and forecast evaluation | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Marc-Oliver Pohle | Organizer: Marc-Oliver Pohle |
| A0495: S. Otto, N. Salish | |
| Approximate factor models for functional time series | |
| A0642: M. Demetrescu, F. Kiessner, M. Knueppel | |
| Simultaneous confidence bands for the PIT histogram | |
| A0957: T. Zahn, M.-O. Pohle | |
| How far can we forecast the economy? | |
| A0970: A. Jordan, T. Gneiting, D. Wolffram, J. Resin, K. Kraus, J. Bracher, T. Dimitriadis, V. Hagenmeyer, S. Lerch, K. Phipps, M. Schienle | |
| Model diagnostics and forecast evaluation for quantiles | |
| A1035: M.-O. Pohle, T. Zahn | |
| Uncertainty quantification in forecast comparisons |
| Session CC495 | Room: 256 |
| Applied econometrics I | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Robinson Kruse-Becher | Organizer: CFE |
| A1732: K. Bien-Barkowska, A. Kliber | |
| An ACD-POT MIDAS model for forecasting extreme returns in oil and metal markets during different economic conditions | |
| A1168: R. Morita, Z. Kurter, P. Gomes | |
| European sovereign bond and stock market Granger causality dynamics | |
| A1174: T. Kobayashi | |
| Term premium in international yield curves: Role of global and local factors | |
| A1188: K. Beck, A. Karadimitropoulou | |
| Lost in aggregation: European, country, sectoral, and regional factors driving the gross value-added fluctuations in EU | |
| A1399: M. Friedrich, S. Telg, P. Ramdaras, B. van der Sluis, Y. Lin | |
| Time-varying effects of housing attributes and economic environment on housing prices |
| Session CC534 | Room: 260 |
| Dynamic factor models | Saturday 16.12.2023 10:00 - 12:05 |
| Chair: Maddalena Cavicchioli | Organizer: CFE |
| A0319: S. Hienzsch, T. Berger | |
| Which global cycle: a stochastic factor selection approach for global macro-financial cycles | |
| A1758: S. Soccorsi, M. Forni, L. Gambetti, A. Granese, S. Luca | |
| An American macroeconomic picture: Supply and demand shocks in the frequency domain | |
| A1716: K. Tsakou, S. Soccorsi | |
| Macroeconomic cycles and bond return predictability | |
| A1774: R. Lacaza, S.J. Villejo | |
| Forecasting Philippine quarterly GDP using dynamic factor model with mixed-frequency data | |
| A1564: A. Karadimitropoulou, L. Ferrara | |
| Commodity price uncertainty co-movement: Does it matter for global economic growth? |
| Parallel session D: CMStatistics | Saturday 16.12.2023 | 13:35 - 15:15 |
| Session EV477 | Room: Virtual R01 |
| Complex data analysis | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Russell Shinohara | Organizer: CFE-CMStatistics |
| B1632: R. Jayamaha, H.B. Kang | |
| Generalized functional linear mixed model | |
| B1912: R. Luo | |
| General nonlinear function-on-function regression via functional universal approximation | |
| B1701: H. Sun, Z. Shang, Y. Chen | |
| Matrix autoregressive model with vector time series covariates for spatiotemporal data | |
| B1809: E. Porter, C. Franck, S. Adams | |
| Flexible cost-penalized Bayesian model selection: Developing inclusion paths with application to medical diagnoses |
| Session EO265 | Room: 227 |
| Statistical methods in weather forecasting | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Sandor Baran | Organizer: Sandor Baran |
| B0213: R. Schefzik | |
| Simulation-based comparison of multivariate postprocessing methods for ensemble weather forecasts | |
| B0513: M. Nagy-Lakatos, S. Baran | |
| Comparison of multivariate post-processing methods using global ECMWF ensemble forecasts | |
| B0539: A. Moeller, D. Jobst, J. Gross | |
| Autoregressive extensions of EMOS with application to surface temperature ensemble postprocessing | |
| B0553: D. Jobst, J. Gross, A. Moeller | |
| D-vine GAM copula based quantile regression with application to ensemble postprocessing |
| Session EO212 | Room: 335 |
| Advances in statistical learning methods and computational statistics | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Julien Hambuckers | Organizer: Julien Hambuckers |
| B0811: L. Trapin, M. Bee, E. Taufer | |
| Tail index regression forest | |
| B1145: H.K. Olafsdottir, D. Bolin, H. Rootzen | |
| Forecast evaluation of extremes using locally tail-scale invariant scoring rules | |
| B1212: J. Brachem, P. Wiemann, T. Kneib | |
| Parametric transformation models for location-scale regression with unknown response distribution | |
| B1247: R. Schmidt, A. Ritz, B. Saefken | |
| Multivariate distributional stochastic frontier models with missing values |
| Session EO088 | Room: 340 |
| Model and copula-based clustering with missing data | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Marta Nai Ruscone | Organizer: Daniel Fernandez, Marta Nai Ruscone |
| B0415: A. Gatto, F.M.L. Di Lascio | |
| A nonparametric copula-based method for the imputation of dependent data | |
| B0645: C. Tortora | |
| Clustering with missing data using normal-scale mixture models | |
| B1052: H. Tong | |
| MixtureMissing: an R package for robust and flexible model-based clustering with incomplete data | |
| B1140: B. Franczak | |
| On an approach for performing model-based clustering and imputation for multivariate data sets with asymmetric features |
| Session EO044 | Room: 348 |
| Emerging questions in network inference | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Vince Lyzinski | Organizer: Vince Lyzinski |
| B0723: K. Levin, A. Hayes | |
| Estimating network-mediated causal effects via spectral embeddings | |
| B0732: J. Cape | |
| On varimax asymptotics in network models and spectral methods for dimensionality reduction | |
| B1204: J. Arroyo, C. James, D. Yuan, I. Gaynanova | |
| Learning joint and individual structure in network data with covariates | |
| B1236: A. Athreya, Z. Lubberts, Y. Park, C. Priebe | |
| Euclidean mirrors and dynamics in network time series |
| Session EO045 | Room: 351 |
| Bayesian and stochastic modeling with complex dependencies | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Alexander Volfovsky | Organizer: Charles Doss |
| B1335: J. Xu | |
| Data-augmented MCMC for learning spatiotemporal transmission structure in epidemic models | |
| B1400: S. Jensen | |
| Spatiotemporal modeling of urban greening | |
| B1473: L. House | |
| Quantifying uncertainty of simulated populations |
| Session EO156 | Room: 352 |
| Advances in dynamic models | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Veronica Ballerini | Organizer: Monia Lupparelli |
| B1191: A. Cassese, W. Zhu, M. Guindani, M. Vannucci | |
| A Bayesian nonparametric spiked process prior for dynamic model selection | |
| B1332: L. Gherardini | |
| Dynamic network models with time-varying nodes | |
| B1358: G. Zens, L. Thalheimer | |
| The short-term dynamics of conflict-driven displacement: Bayesian modeling of disaggregate Data from Somalia | |
| B1551: M.N. Damian, C. Ley, J. Hale | |
| Using optimal transport to assess the impact of prior choice on Bayesian parameter inference in dynamical systems |
| Session EO315 | Room: 353 |
| Advanced estimation techniques in sample surveys | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Francesco Schirripa Spagnolo | Organizer: Francesco Schirripa Spagnolo |
| B0266: A. Moretti | |
| Multivariate small area estimation in case of non-continuous variables | |
| B0454: L. mori, M.R. Ferrante | |
| Small area estimation of economic indicators under unit-level generalized additive models for location, scale and shape | |
| B0604: J. Sakshaug, C. Salvatore, A. Wisniowski, B. Struminskaya, S. Biffignandi | |
| Integrating data from multiple surveys to improve estimation | |
| B0391: S. Harmening, M. Runge, T. Schmid | |
| Area-level small area estimation with random forests | |
| B0516: M. Dagdoug, D. Haziza | |
| Variance estimation for survey estimators based on statistical learning procedures |
| Session EO285 | Room: 354 |
| Novel methods and practical strategies for clinical trials | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Andrew Spieker | Organizer: Andrew Spieker |
| B1323: B. Blette, B. Kahan, M. Harhay, F. Li | |
| Evaluating informative cluster size in cluster randomized trials | |
| B1379: M. Bannick, T. Ye, J. Shao, Y. Yi, J. Liu, Y. Du | |
| A novel covariate adjustment strategy for guaranteed efficiency gain in randomized clinical trials | |
| B1395: A. Stephens Shields | |
| Advancing clinical trial design in syndromic diseases with observational data | |
| B1475: J. Chipman, L. Mayberry, R. Greevy | |
| Sequential matched randomization to personalize randomization and improve covariate balance and trial efficiency |
| Session EO309 | Room: 355 |
| Recent advances in learning from complex data | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Xin Bing | Organizer: Xin Bing |
| B0428: M. Pensky | |
| Clustering of diverse multiplex networks | |
| B0501: M. Wegkamp, X. Bing | |
| Discriminant analysis in high-dimensional Gaussian mixtures | |
| B1160: Y. Gu, L. Chen | |
| A spectral method for identifiable grade of membership analysis in high dimensions | |
| B1234: P. Zwiernik | |
| Entropic covariance models |
| Session EO200 | Room: 356 |
| Design and analysis of experiments (virtual) | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: John Stufken | Organizer: John Stufken |
| B0386: W. Zheng, X. Zhang, L. Gao | |
| Thompson sampling with discrete prior | |
| B0733: N. Rios | |
| Graphical methods for order-of-addition experiments | |
| B0863: L. Wang | |
| Active labeling for high-dimensional ridge regression with application in genome-wide association studies | |
| B0480: R. Singh | |
| Design selection for multi- and mixed-level supersaturated designs |
| Session EO294 | Room: 357 |
| Extremes and machine learning | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Antoine Usseglio-Carleve | Organizer: Antoine Usseglio-Carleve, Stephane Girard |
| B0394: A. Heranval, M. Thomas, O. Lopez | |
| Generalized Pareto regression trees for extreme event analysis | |
| B0705: X. Shao, J. Richards, R. Huser | |
| Deep compositional models for nonstationary extremal dependence | |
| B1119: M. Allouche, E. Gobet, S. Girard | |
| Estimation of extreme expected shortfall with neural networks | |
| B1163: G. Stupfler, A. Usseglio-Carleve, A. Daouia | |
| Inference for extremal regression with dependent heavy-tailed data |
| Session EO404 | Room: 401 |
| Healthcare analytics: Risk prediction, fairness, and federated learning | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Chuan Hong | Organizer: Chuan Hong |
| B0203: M. Liu, D. Zhou, T. Cai | |
| Robust and efficient transfer learning of high dimensional EHR-linked biobank data | |
| B0898: S. Li | |
| FedScore: A privacy-preserving framework for federated scoring system development | |
| B1020: B. Vakulenko-Lagun | |
| Federated regression analysis of heterogeneous data with competing risks | |
| B1308: J. Zhao | |
| Evaluating the algorithmic fairness for cardiovascular risk prediction model |
| Session EO238 | Room: 403 |
| Statistical innovations in scRNA-seq and spatial transcriptomics analysis | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Yuehua Cui | Organizer: Yuehua Cui |
| B1866: K. Coleman, J. Hu, D. Zhang, M. Li | |
| Analysis of multi-modal spatial omics with MISO | |
| B1947: S. Sun | |
| Powerful and accurate detection of temporal gene expression patterns from multi-sample multi-stage scRNA-seq data | |
| B1699: J. Li | |
| Quantitative estimation of cell-phenotype associations | |
| B1253: L. Shang, X. Zhou | |
| Spatially aware dimension reduction for spatial transcriptomics |
| Session EO229 | Room: 404 |
| Spatial statistics meets machine and statistical learning | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Veronica Berrocal | Organizer: Veronica Berrocal |
| B0996: L. Patelli, M. Cameletti, N. Golini, R. Ignaccolo | |
| Random forest in the spatial framework, how to deal with it? | |
| B0217: M. Heaton | |
| On the use of mini-batching for fitting Gaussian processes | |
| B1135: F. Denti | |
| Multi-resolution approximation via flexible cumulative shrinkage processes: The CUSP-MRA prior | |
| B0568: B. Jin, D. Dunson | |
| A unified Bayesian approach to overcome spatial confounding in point-referenced data |
| Session EO249 | Room: 414 |
| Using social media to enhance survey research | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Annamaria Bianchi | Organizer: Annamaria Bianchi |
| B0768: C. Salvatore, A. Bianchi, S. Biffignandi | |
| Social media in survey research | |
| B1422: F. Conrad | |
| Finding alignment between social media and survey responses | |
| B0840: T. Al Baghal, P. Serodio, S. Liu, L. Sloan, C. Jessop | |
| Using social media metrics and linked survey data to understand survey behaviors | |
| B0995: L. Calderwood | |
| Using social media for participant engagement and tracking in longitudinal surveys |
| Session EO091 | Room: 424 |
| Modern directional statistics | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Andrea Meilan-Vila | Organizer: Andrea Meilan-Vila |
| B0617: A. Bekker, D. van Wyk de Ridder, J. Ferreira, P. Nagar | |
| A skew normal model for consideration on the sphere | |
| B0676: J.E. Chacon, A. Meilan-Vila | |
| A geodesic normal distribution on the sphere with elliptical contours | |
| B0771: F. Lagona, M. Mingione | |
| Segmenting toroidal time series by non-homogeneous hidden semi-Markov models | |
| B0959: S. Fensore, M. Di Marzio, A. Panzera, C. Taylor | |
| Local circular regression with errors-in-variables |
| Session EO066 | Room: 442 |
| Advances in modelling complex dependence structures | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Cristina Mollica | Organizer: Cristina Mollica |
| B1262: C. Garcia-Gomez, F. Durante, A. Perez Espartero, M. Prieto-Alaiz | |
| Contagion of deprivations and affluences: A tail dependence story | |
| B1491: O. Sorensen | |
| Generalized additive latent and mixed models | |
| B1708: M. Stefanucci, M. Stefanucci, A. Farcomeni | |
| Topic characterization and distinction using constrained latent Dirichlet allocation | |
| B1639: H. Ogden | |
| Flexible models for longitudinal data |
| Session EO527 | Room: 444 |
| Methodology for structured data | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Ranjan Maitra | Organizer: Ranjan Maitra |
| B0665: A. Murua, V. Partovi Nia | |
| Neural networks on the edge: Performance under compression | |
| B0448: E. Lock | |
| Integrative regression and factorization of bidimensionally linked matrices | |
| B0993: C. Llosa, D.M. Dunlavy, R.B. Lehoucq, A. Prasadan, O. Lopez | |
| Cramer-Rao bounds for CANDECOMP/PARAFAC non-negative tensor decomposition | |
| B0567: S. Dutta, S. Pal | |
| Spatial factor models based on fractional Gaussian fields |
| Session EO098 | Room: 445 |
| Clustered data analysis and related topics | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Sanjoy Sinha | Organizer: Sanjoy Sinha |
| Session EO086 | Room: 446 |
| Distributional shifts and applications to missing data and causal inference | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Xavier de Luna | Organizer: Xavier de Luna |
| B0406: Y. Ma | |
| Doubly flexible estimation under label shift | |
| B1543: M. Ghasempour, Y. Ma, X. de Luna | |
| A generalized label shift model for robust estimation: Predicting cohorts hospitalizations | |
| B0312: J. Zhao | |
| ELSA: efficient label shift adaptation through the lens of semiparametric models | |
| B0479: S. Saengkyongam | |
| Effect-invariant mechanisms for policy generalization |
| Session EO129 | Room: 447 |
| Regression modeling with objects in metric spaces (virtual) | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Changbo Zhu | Organizer: Alexander Petersen |
| B0717: M. Matabuena, G. Lugosi | |
| Uncertainty quantification in metric spaces | |
| B0208: Z. Lin, Y. Lin | |
| Logistic regression and classification with non-Euclidean covariates | |
| B0835: R. Qiu, Z. Yu, R. Zhu | |
| Random forest weighted local Frechet regression with random objects | |
| B0793: C. Zhu, H.-G. Mueller | |
| Autoregressive models for distributional time series |
| Session EO125 | Room: 455 |
| Recent advances in GWAS | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Linxi Liu | Organizer: Linxi Liu |
| B1702: S. Ma | |
| Knockoff-based statistics for the identification of putative causal genes in genetic studies | |
| B1372: Z. Yang, L. Liu, I. Ionita-Laza | |
| CARMA: Novel Bayesian model for fine-mapping in GWAS meta-analyses and multi-ethnic | |
| B1634: J. Gu, Z. He | |
| A powerful and precise filter of feature selection using group knockoffs | |
| B1637: L. Yi, L. Liu | |
| Identification of differentially expressed genes via knockoff statistics in single-cell RNA sequencing data analysis |
| Session EO102 | Room: 457 |
| High-dimensional complex data modeling, causality and beyond | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Chenlu Ke | Organizer: Chenlu Ke |
| B1963: Y. Yuan | |
| De-confounding causal inference using latentmultiple-mediator pathways | |
| B1139: J. Weng | |
| Frechet sufficient dimension reduction and variable selection | |
| B1795: B. Cai | |
| Jointly modeling and clustering tensors in high dimensions | |
| B0426: I. Sahoo, J. Guinness, B. Reich | |
| Estimating atmospheric motion winds from satellite image data using spacetime drift models |
| Session EO166 | Room: 458 |
| HiTEc: Recent advances in model specification testing | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Bojana Milosevic | Organizer: Bojana Milosevic |
| B1138: M. Cuparic, B. Milosevic, B. Ebner | |
| Testing independence for circular data: Energy-based approach | |
| B1499: J. Visagie, J. Allison, S. Meintanis, L. Snyman | |
| A new test of fit for one-sided stable laws based on the Laplace transform | |
| B1648: V.S. Barbu, T. Gkelsinis | |
| A class of hypothesis tests for general order Markov chains based on phi-divergence | |
| B1867: D. Aleksic | |
| A new approach to Little's MCAR test |
| Session EO087 | Room: Virtual R02 |
| Bayesian inference for complex models | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: David Nott | Organizer: David Nott |
| B0385: A. Zammit Mangion, M. Sainsbury-Dale, J. Richards, R. Huser | |
| Neural Bayes estimators for irregular spatial data using graph neural networks | |
| B0775: N. Klein, M.S. Smith, D. Nott | |
| Deep distributional time series models and the probabilistic forecasting of intraday electricity prices | |
| B1117: H. Wagner | |
| Factor-augmented time-varying coefficents panel data models | |
| B0234: B. Reich, R. Majumder, B. Shaby | |
| Modeling extremal streamflow using deep learning approximations and a flexible spatial process |
| Session EO266 | Room: Virtual R03 |
| Advanced statistical methods and applications in complex data analysis | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Yichuan Zhao | Organizer: Yichuan Zhao |
| Parallel session D: CFE | Saturday 16.12.2023 | 13:35 - 15:15 |
| Session CV500 | Room: Virtual R04 |
| Computational and financial econometrics | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Wenbo Wu | Organizer: CFE |
| A1404: I. Kovalenko, T. Conlon, J. Cotter | |
| Regular vine copula-based portfolio optimization | |
| A1801: F. Alshahrani | |
| Nonparametric functional risk measurements with application to NASDAQ index | |
| A1743: M. Webb | |
| Using images as covariates: Measuring curb appeal with deep learning | |
| A1815: T. Brough, J. Goodridge | |
| An operational-subjective model of options arbitrage |
| Session CI014 (Special Invited Session) | Room: 350 |
| Advances in time series analysis | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Joann Jasiak | Organizer: Joann Jasiak |
| A0161: N. Meddahi | |
| Non-linear time series models and machine learning | |
| A0432: M. Carrasco, C. Nokho | |
| Hansen-Jagannathan distance with many assets | |
| A0163: Y. Chang, S. Kim, J. Park | |
| A novel structural mixed autoregression with aggregate and functional variables |
| Session CO018 | Room: 236 |
| Time series econometrics | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Antonio Montanes | Organizer: Antonio Montanes |
| A0850: L. Gadea | |
| Local projections inference (preliminary version) | |
| A1549: M. Camarero, J.L. Carrion-i-Silvestre, C. Tamarit | |
| Current account determinants in a globalized world | |
| A1909: P. Poncela, E. Senra, J. Bogalo | |
| Understanding fluctuations through multivariate circulant singular spectrum analysis | |
| A1848: A. Montanes | |
| Estimating trends under non-stationary heteroskedasticity |
| Session CO295 | Room: 256 |
| Cross-sectional asset pricing | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Valentina Raponi | Organizer: Valentina Raponi, Paolo Zaffaroni |
| A0325: S. Kim, P. Zaffaroni, V. Raponi | |
| Testing for weak factors in asset pricing | |
| A0548: M. Pelger, D. Filipovic, Y. Ye | |
| Shrinking the term structure | |
| A0566: S. Giglio, D. Xiu | |
| Test assets and weak factors | |
| A0638: P. Schneider, D. Filipovic, M. Multerer | |
| Conditional factor structures on large asset markets |
| Session CO029 | Room: 257 |
| AI for Energy Finance - AI4EFin II | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Alla Petukhina | Organizer: Alla Petukhina |
| A1823: V. Bolovaneanu, A.-I. Moukas, A. Petukhina, D.T. Pele, N. Thomaidis | |
| Optimizing wind energy aggregation: a comparative analysis of asset allocation techniques | |
| A1825: A. Conda, A. Petukhina, A. Melzer, M. Phan, M. Basangova, S. Alkhoury, V. Bolovaneanu | |
| Day-ahead probability forecasting for redispatch | |
| A1892: S. Lessmann, G. Velev | |
| Neural architecture search for bitcoin market prediction | |
| A1888: C.O. Cepoi, A.A. Cramer, R. Clodnitchi, D.T. Pele, V. Strat, S. Anagnoste | |
| Forecasting realized volatility using machine learning: The case of EU energy listed firms |
| Session CO146 | Room: 258 |
| Regime switching, filtering and portfolio optimization | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Joern Sass | Organizer: Joern Sass |
| A0679: L. Gruber, F. Huber, G. Kastner | |
| Dynamic sparsity in factor stochastic volatility models | |
| A0856: M. Phan, J. Sass, C. Erlwein-Sayer | |
| Regime dependent jump frequencies in cryptocurrency log returns | |
| A0918: M. Scholz, J.P. Nielsen, M. Marchese, M.D. Martinez-Miranda | |
| Robustifying and simplifying high-dimensional regression: Applications to financial returns and telematics data | |
| A0925: J. Sass | |
| Utility maximization in a continuous-time financial market: Filtering and uncertainty |
| Session CO155 | Room: 259 |
| Financial risks in green transition: Greenness-at-Risk | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Juan-Angel Jimenez-Martin | Organizer: Juan-Angel Jimenez-Martin |
| A0264: L. Garcia-Jorcano, L. Sanchis-Marco | |
| Measuring the impact of climate risk in financial markets: A joint quantile and expected shortfall regression model | |
| A0270: L. Sanchis-Marco, L. Garcia-Jorcano | |
| Measuring the impact of climate transition risk in the systemic risk: A multivariate quantile-located ES approach | |
| A0962: A.M. Garcia Sanz | |
| Does the gender diversity affect downside and tail risks? An analysis of US and European firms | |
| A1022: J.-A. Jimenez-Martin, R. Yang, M. Caporin | |
| Chasing the non-linear ESG factor |
| Session CO027 | Room: 260 |
| Uncertainty in macroeconomics and empirical finance | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Etsuro Shioji | Organizer: Etsuro Shioji |
| A0336: K.-I. Inaba | |
| A global look into corporate cash valued in stock indices over the recent decade | |
| A0399: J. Oh, A. Rogantini Picco | |
| Macro uncertainty, unemployment risk, and consumption dynamics | |
| A0879: M. Shintani, T. Fueki, T. Shinohara | |
| International comparison of climate change news index with an application to monetary policy | |
| A0403: E. Shioji | |
| Yield curve control under attack: Where do the pressures come from? |
| Session CO343 | Room: 261 |
| Recent developments in financial modelling and forecasting | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Ekaterini Panopoulou | Organizer: Ekaterini Panopoulou |
| A1459: J. Oberoi, N. Voukelatos, X. Sun | |
| Forecasting market returns with implied correlation: The benefits of using horizon-specific information | |
| A1448: E. Panopoulou, A. Alexandridis, I. Souropanis | |
| Forecasting exchange rate realized volatility: An amalgamation approach | |
| A1598: C. Argyropoulos | |
| Predicting hedge funds returns | |
| A1449: S. Vrontos, E. Panopoulou, I. Vrontos, J. Galakis | |
| Forecasting GDP growth: The economic impact of COVID-19 Pandemic |
| Session CO358 | Room: 262 |
| Portfolio choice | Saturday 16.12.2023 13:35 - 15:15 |
| Chair: Rainer Alexander Schuessler | Organizer: Rainer Alexander Schuessler |
| A0588: N. Lassance, A. Martin-Utrera | |
| Shrinking against sentiment: Exploiting latent asset demand in portfolio selection | |
| A0758: H. Nyberg, L. Nevasalmi | |
| Moving forward from predictive regressions: Boosting asset allocation decisions | |
| A1001: E. Platanakis, G. Zhou, X. Ye, A.J. Hou | |
| Commodity inflation risk premium and stock market returns | |
| A1007: P. Goulet Coulombe, M. Goebel | |
| Maximally machine-learnable portfolios |
| Parallel session E: CMStatistics | Saturday 16.12.2023 | 15:45 - 17:00 |
| Session EO286 | Room: 340 |
| Recent developments in clustering for complex data structure | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Antonello Maruotti | Organizer: Monia Ranalli |
| B0609: M.B. Ferraro, P. Giordani, M. Vichi | |
| Fuzzy Pseudo-F: One- and two-mode clustering cases | |
| B1179: P. Alaimo Di Loro, M. Mingione, L. Tardella, G. Jona Lasinio, D.S. Pace, G. Caruso | |
| Finite mixtures in capture-recapture surveys for modelling residency patterns in marine wildlife populations | |
| B1576: G. Zaccaria, F. Greselin, A. Mayo-Iscar | |
| Model-based clustering with cellwise outliers and missing data |
| Session EO377 | Room: 348 |
| Recent development in statistical network analysis | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Can Minh Le | Organizer: Can Minh Le |
| B0824: Z. Lubberts, A. Athreya, C. Priebe, Y. Park | |
| Beyond the adjacency matrix: Random line graphs and inference for networks with edge attributes | |
| B1679: C. Miglioli, P.A. Della Rosa, M.-P. Victoria-Feser, S. Guerrier | |
| Two-sample permutation tests for graphical models and random graphs, with applications to brain connectivity | |
| B0431: R. Rastelli, C. Jiang, D. La Vecchia | |
| A multiview network model for commodities trading data |
| Session EO255 | Room: 350 |
| Semiparametric and ordinal regression models | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Jonathan Schildcrout | Organizer: Jonathan Schildcrout |
| B1582: R. Tao | |
| Efficient designs and analysis of two-phase studies with longitudinal binary data | |
| B1838: C. Di Gravio, R. Tao, J. Schildcrout | |
| Analysis of ordinal longitudinal data under case-control sampling: Studying mortality in critically ill patients | |
| B1955: P. Rathouz, E. Alam, P. Mueller | |
| Bayesian analysis and inference for semiparametric generalized linear models with discrete or continuous data |
| B0322: R. Seymour | |
| Bayesian nonparametric methods for individual level stochastic epidemic models | |
| B0457: P. De Blasi | |
| Gibbs sampling for mixtures in order of appearance: The ordered allocation sampler | |
| B1360: R. Argiento, A. Guglielmi, R. Corradin | |
| Mixtures of product partition models with covariates to cluster blood donors |
| Session EO160 | Room: 352 |
| Novel perspectives in Bayesian statistics (virtual) | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Pier Giovanni Bissiri | Organizer: Pier Giovanni Bissiri |
| B0565: M. Cannas, G. Puggioni | |
| On the Voigt profile and its dual | |
| B0944: A. Datta | |
| Generalized Bayes for compositional data | |
| B1161: P.G. Bissiri, S. Walker | |
| Statistical inference with conditionally identically distributed observations |
| Session EO181 | Room: 353 |
| Uncertainty quantification via sampling and optimization | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Yifan Cui | Organizer: Yifan Cui |
| B0294: J. Hannig | |
| A geometric perspective on Bayesian and generalized fiducial inference | |
| B0311: H. Iyer, S. Lund, D. Newton | |
| Exploring model uncertainty using linear programming | |
| B1000: G. Li, J. Hannig | |
| Deep fiducial inference |
| Session EO268 | Room: 354 |
| Advanced methods and applications of time-to-event data in health research | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Samuel Manda | Organizer: Samuel Manda |
| B0338: S. Manda | |
| Iterative generalized least squares estimation for the analysis of multilevel interval-censored survival data | |
| B1205: N. Nakhaeirad, V. Fakoor, D. Chen | |
| Goodness of fit tests for partly interval censored survival data | |
| B1683: T.H. Nguyen | |
| Predicting risk groups for time to event data using microbiome biomarkers: Methodology and software development |
| Session EO373 | Room: 355 |
| Developments in sufficient dimension reduction and statistical networks | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Shanshan Ding | Organizer: Shanshan Ding |
| B1329: W. Luo | |
| On efficient dimension reduction with respect to the interaction between two response variables | |
| B0547: Y. Zhao, J. Fan, W. Wang | |
| A significance test for feature variables through deep neural networks | |
| B1018: P. Zhao, A. Bhattacharya, D. Pati, B. Mallick | |
| Factorized fusion shrinkage for dynamic relational data |
| Session EO092 | Room: 356 |
| Advances in Bayesian methodology | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Riccardo Corradin | Organizer: Riccardo Corradin |
| B0573: M. Beraha | |
| Learning to approximately count with Bayesian non-parametrics | |
| B1085: A. Mascaro, F. Castelletti | |
| Bayesian causal discovery from unknown general interventions | |
| B0621: S. Power | |
| Explicit convergence bounds for Metropolis Markov chains |
| Session EO435 | Room: 357 |
| Spatial and spatiotemporal peaks-over-threshold with flexible models II | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Thomas Opitz | Organizer: Thomas Opitz |
| B0754: M. Thannheimer, M. Oesting | |
| Bayesian inference for functional extreme events defined via partially unobserved processes | |
| B0756: D. Allard, L. Clarotto, X. Emery | |
| Fully non-separable Gneiting covariance functions for multivariate space-time data | |
| B0817: T. Opitz | |
| Modeling multivariate space-time extreme-event episodes with r-Pareto processes |
| Session EO283 | Room: 401 |
| Branching and related processes II | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Ines M del Puerto | Organizer: Ines M del Puerto, Miguel Gonzalez Velasco |
| B1277: G. Francisci, A. Vidyashankar | |
| Empirical processes on trees and applications to depth functions | |
| B1668: E. Yarovaya | |
| Continuous time multitype branching random walks | |
| B1814: M. Gonzalez Velasco, P. Martin-Chavez, I.M. del Puerto, M. Serrano Pastor | |
| Particle filtering methods for partially observed branching processes |
| Session EO441 | Room: 403 |
| Optimization for statistical learning (virtual) | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Ana Kenney | Organizer: Ana Kenney |
| B1193: T. Tang, G. Allen | |
| Integrated principal components analysis | |
| B0953: A. Gomez | |
| Outlier detection in regression via mixed-integer optimization |
| Session EO109 | Room: 404 |
| New advances in spatial and environmental statistics | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Rajarshi Guhaniyogi | Organizer: Rajarshi Guhaniyogi |
| Session EO049 | Room: 414 |
| Statistical modeling in neuroimaging | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: John Kornak | Organizer: John Kornak |
| B1238: P.V. Redondo, R. Huser, H. Ombao | |
| Spectral causation entropy | |
| B1334: F. Jiang | |
| Dynamic functional connectivity MEG features of Alzheimer's disease | |
| B1555: J. Harezlak, M. Dzemidzic, D. Kareken, X. Xu | |
| Novel penalized regression method applied to study the association of brain functional connectivity and alcohol drinking |
| Session EO384 | Room: 424 |
| Modern approaches to directional data analysis | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Stefania Fensore | Organizer: Stefania Fensore |
| B0780: C. Passamonti, M. Di Marzio, S. Fensore | |
| On detecting data Benfordness | |
| B1114: P. Nagar, A. Bekker, M. Arashi | |
| Regularized maximum likelihood for data on the sphere |
| Session EO385 | Room: 442 |
| Challenges in categorical data | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Silvia Angela Osmetti | Organizer: Andrea Bonanomi, Silvia Angela Osmetti |
| B0533: F. Rapallo | |
| Normalizing the weighted kappa in rater agreement problems | |
| B0636: O. Epifania, P. Anselmi, E. Robusto | |
| When randomness opens new possibilities: acknowledging the stimulus sampling variability in experimental psychology | |
| B0884: B. Zumbo | |
| The role of the distribution of categorical responses to survey questions on psychometric dimensionality assessment |
| Session EO360 | Room: 444 |
| New advances in Bayesian methodology | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Jairo Fuquene | Organizer: Jairo Fuquene |
| B1612: P. Touloupou, S. Spencer, B. Finkenstadt | |
| Scalable inference for epidemic models with individual level data | |
| B1722: S. Guha | |
| A Bayesian approach to network classification | |
| B1906: X. Tang, M. Ghosh | |
| Global-local priors for spatial small area estimation |
| Session EO230 | Room: 445 |
| Targeted machine learning and causal inference : Applications in medicine | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Stathis Gennatas | Organizer: Stathis Gennatas |
| B1488: L. van der Laan, M. Carone, A. Luedtke, M. van der Laan | |
| Adaptive debiased machine learning using data-driven model selection techniques | |
| B1868: Z. Wang, W. Zhang, M. van der Laan | |
| Super ensemble learning using the highly-adaptive-lasso | |
| B1953: G. Valdes | |
| Targeted learning to predict toxicity impact on survival in advanced lung cancer patients |
| Session EO219 | Room: 446 |
| Conditional independence testing and causal inference | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Nabarun Deb | Organizer: Nabarun Deb |
| B0877: Z. Huang, N. Deb, B. Sen | |
| Kernel partial correlation coefficient: A measure of conditional dependence | |
| B1547: I. Kim, M. Neykov, S. Balakrishnan, L. Wasserman | |
| Local permutation tests for conditional independence | |
| B1586: A. Ghosh, N. Deb, B. Karmakar, B. Sen | |
| Efficiency and robustness of Rosenbaum's regression (un)-adjusted rank-based estimator in randomized experiments |
| Session EO405 | Room: 447 |
| Recent advances in functional data analysis | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Surajit Ray | Organizer: Surajit Ray |
| B0288: S. Ray, M. Al Alawi, M. Gupta | |
| A new functional data clustering technique based on spectral clustering and downsampling | |
| B0589: G. Hooker, E. Gunning | |
| A new understanding of principal differential analysis | |
| B0899: C. Wilkie, S. Ray, C. Miller, M. Scott | |
| A historical functional linear model in the spatiotemporal setting of a flowing river |
| Session EO114 | Room: 457 |
| Developments in regression analysis for big and/or high-dimensional data | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Olcay Arslan | Organizer: Olcay Arslan |
| B0905: Y. Tuac, P. Filzmoser, O. Arslan | |
| Robust parameter estimation, variable selection in the ultra-high dimensional regression with autoregressive error terms | |
| B0932: O. Arslan, Y. Guney | |
| Robust parameter estimation and variable selection in regression models when heteroscedasticity and skewness are present | |
| B1282: N. Martin, J.M. Marin | |
| Lagrange multipliers specification test for high dimensional one-way random-effects models |
| Session EO179 | Room: 458 |
| HiTEc: Structured multivariate and functional data | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Michal Pesta | Organizer: Michal Pesta, Matus Maciak |
| B1273: M. Huskova | |
| Detection of changes in panel data models | |
| B1385: S. Gavioli-Akilagun, P. Fryzlewicz | |
| Fast and optimal inference for change points in piecewise polynomials via differencing | |
| B1390: M. Pesta, M. Huskova | |
| Regime changes and unsupervised learning |
| Session EO050 | Room: Virtual R02 |
| Advances in empirical Bayes methodology | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Asaf Weinstein | Organizer: Asaf Weinstein |
| B1703: T. Banerjee, P. Sharma | |
| Nonparametric empirical Bayes prediction in mixed models | |
| B1829: S.D. Zhao | |
| Strategies for high-dimensional empirical Bayes problems | |
| B1893: Z. Zhao, X. Xing | |
| On the model-free testing of multiple hypothesis in sliced inverse regression |
| Session EO314 | Room: Virtual R03 |
| Recent advances in statistical learning and analysis for complex data | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Lan Gao | Organizer: Lan Gao |
| B0299: D. Leung, Q.-M. Shao | |
| Uniform and nonuniform Berry-Esseen bound for Studentized U-statistics | |
| B0525: X. Dai | |
| Kernel ordinary differential equations | |
| B0980: S. Yu, G. Wang, L. Wang | |
| Distributed heterogeneity learning for generalized partially linear models with spatially varying coefficients |
| Session EC548 | Room: 335 |
| Statistical models for dependence I | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Elisa Perrone | Organizer: Elisa Perrone |
| B1562: U. Can, R. Laeven, J. Einmahl | |
| Two-sample testing for tail copulas with an application to equity indices | |
| B1693: I. Gijbels, S. De Keyser | |
| Copula-based measures for dependence between random vectors | |
| B1854: H. Cossette | |
| Collective risk models with FGM dependence |
| Session EC546 | Room: 455 |
| Multivariate and functional time series | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Andrej Srakar | Organizer: CFE-CMStatistics |
| B1610: M. Sauvenier | |
| Multivariate multiscale model for locally stationary processes | |
| B1766: C.T. Ng, Y. Wu | |
| Admixture analysis of multi-site multivariate time series | |
| B0537: B. Wouters | |
| Noise reduction for functional time series |
| Parallel session E: CFE | Saturday 16.12.2023 | 15:45 - 17:00 |
| Session CV496 | Room: Virtual R04 |
| Applied econometrics | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Genaro Sucarrat | Organizer: CFE |
| A0561: S. Siagh | |
| Should resource rich countries launch a SWF? The key role of nation's income level and capital stock | |
| A1816: Y.-Y. Wong | |
| Venture capital exit: A dynamic duration approach | |
| A1998: D. Chandrashekhar, S. Chan | |
| The financial impact of war on commodities |
| Session CO533 | Room: 227 |
| Applied machine learning and forecasting | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Simone Maxand | Organizer: Simone Maxand |
| A0765: U. Frey, F. Nitsch, E. Sperber, E.G. Achraf, F. Miorelli, C. Schimeczek, A. Kaya, S. Rebennack | |
| Forecasting multiple attributes considering uncertainties in a coupled energy systems model | |
| A1170: J. Schwenzer | |
| Neural network water inflow modelling: Predicting Colombian hydropower generation capacities | |
| A1452: S. Maxand, J. Schwenzer, T. Grandon | |
| oraklE$\_$R: An R package for long-term energy demand forecasting |
| Session CO372 | Room: 236 |
| Quantitative methods in investment management | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Gaelle Le Fol | Organizer: Serge Darolles, Gaelle Le Fol |
| A0673: A. Thomas | |
| Learning the predictive density of mixed-causal ARMA processes for portfolio optimization | |
| A0778: L. Dumontier, C. De Franco | |
| Yes, Virginia, there is still hope: Twenty years of sector rotation with Shiller's CAPE ratio | |
| A0839: J. Coadou, S. Darolles | |
| Does ESG matter more than the TE? |
| Session CO389 | Room: 256 |
| Contemporary issues in modelling for environmental sustainability | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Michail Karoglou | Organizer: Michail Karoglou |
| A0901: M. Karoglou, I. El Kalak, A. Azevedo | |
| Wind energy price-quantity correlation: A gift of nature | |
| A0904: M. Tsagris | |
| Factors shaping innovative behavior: A meta-analysis of technology adoption studies in agriculture | |
| A0940: B. Morley | |
| Will the energy transition lead to higher housing prices? Estimation with panel data |
| Session CO413 | Room: 257 |
| AI for Energy Finance - AI4EFin I | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Stefan Lessmann | Organizer: Stefan Lessmann |
| A1719: A. Petukhina, I. Agakishev, K. Kozmik, W.K. Haerdle, M. Kopa | |
| Multivariate probabilistic forecasting of electricity prices with trading applications | |
| A1780: A.-V. Andrei, D.T. Pele | |
| Deep learning for energy forecasting: A benchmark | |
| A1822: R.-A. Grecu, D.T. Pele, A.A. Cramer | |
| The impact of energy prices on stock returns in selected Central and Eastern European countries |
| Session CO316 | Room: 259 |
| New approaches to volatility dynamics and financial fragility | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Giorgia Rivieccio | Organizer: Giorgia Rivieccio |
| A0579: M. Brunetti, C. Torricelli, E. Giarda | |
| Financial fragility across Europe: Is it the household or the country that matters? | |
| A0618: G. De Luca, G. Rivieccio | |
| NFTs transaction dynamics and sentiment analysis | |
| A0690: A. Pacifico | |
| Financial modeling under non-Gaussian distribution |
| Session CO188 | Room: 260 |
| Applied macro-finance | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Alessia Paccagnini | Organizer: Alessia Paccagnini |
| A0486: M. Cacciatore, G. Candian | |
| Uncertainty through the production network: Evidence from stock market data | |
| A0887: G. Nicolo, F. Bianchi, D. Song | |
| Inflation and real activity over the business cycle | |
| A1621: A. Paccagnini, F. Parla | |
| Financial conditions for the US: Aggregate supply or aggregate demand shocks? |
| Session CO392 | Room: 261 |
| Topics in applied econometrics | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Eiji Goto | Organizer: Saeed Zaman |
| Session CO278 | Room: 262 |
| Spatial statistic and econometric models (virtual) | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Maria Michela Dickson | Organizer: Maria Michela Dickson |
| A0663: D. Giuliani, M.M. Dickson, G. Espa, F. Santi | |
| Adjusting for neighboring effects in measuring industry coagglomeration | |
| A0927: A. Cartone, A. Di Isidoro, P. Postiglione | |
| Spatial filtering techniques for the definition of spatial non-compensatory indices | |
| A0650: J. Dube, D. Doloreux, R. Shearmur, D. Cardenas | |
| The city and KIBS clusters: A microgeographic analysis for Montreal |
| Session CO426 | Room: Virtual R01 |
| Advances in high-dimensional data analysis | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Seungchul Baek | Organizer: Seungchul Baek |
| A1946: S. Baek, J. Park, H. Park | |
| Variable selection for PFC Models in high dimensions | |
| A0726: H.C. Chung, Y. Ni, I. Gaynanova | |
| Sparse semiparametric discriminant analysis for high-dimensional zero-inflated data | |
| A0736: Y. Wu, L. Wang, B. Wu, Y. Ye, H. Zhao | |
| Robust high-dimensional inference for causal effects under unmeasured confounding and invalid IVs |
| Session CC535 | Room: 258 |
| Portfolio management | Saturday 16.12.2023 15:45 - 17:00 |
| Chair: Ralf Wilke | Organizer: CFE |
| A1609: S. Arvanitis, O. Scaillet, N. Topaloglou | |
| Sparse spanning portfolios and under-diversification with second-order stochastic dominance | |
| A1937: N. Topaloglou | |
| GDP-linked bonds as a new asset class | |
| A1834: A. Brou, R. Luger | |
| The economic value of reward-to-risk timing strategies using return-decomposition GARCH models |
| Parallel session F: CMStatistics | Saturday 16.12.2023 | 17:10 - 18:50 |
| Session EO192 | Room: 261 |
| Developments of computational statistics for financial applications | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Lorenzo Mercuri | Organizer: Lorenzo Mercuri |
| B0614: Y. Koike | |
| Estimation of the number of relevant factors from high-frequency data | |
| B0688: E. Rroji, L. Mercuri, A. Perchiazzo | |
| Bivariate CARMA-Hawkes model: Theory and applications | |
| B0735: Y. Uehara | |
| Predictive model selection for jump diffusion models | |
| B0844: F. Iafrate | |
| Pathwise optimization for adaptive Bridge-type estimators: applications to stochastic differential equations |
| Session EO439 | Room: 335 |
| Semiparametric models for dependent data | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Donatello Telesca | Organizer: Donatello Telesca |
| B0481: X. Zhou, J. Wrobel, C. Crainiceanu, A. Leroux | |
| Generalized multilevel functional principal component analysis | |
| B1113: V. Berrocal | |
| Understanding crop vulnerability to soil moisture extreme conditions | |
| B1151: E. Lila, J. Buenfil | |
| Integrative analysis of functional and high-dimensional data | |
| B1511: M. Guindani | |
| Semi-parametric local variable selection under misspecification |
| Session EO169 | Room: 340 |
| Clustering of categorical and mixed data II | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Giovanna Menardi | Organizer: Giovanna Menardi |
| B0652: C. Hennig, K. Murphy | |
| Quantifying variable importance in cluster analysis | |
| B0928: N. Corsini, G. Menardi | |
| Clustering of categorical data via mutual information | |
| B1120: D. De Stefano, S. Geremia | |
| Investigating the impact of content similarity on density-based clustering of social networks | |
| B1155: M. Markatou | |
| Clustering mixed-type data |
| Session EO421 | Room: 348 |
| Network models with latent structure | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Keith Levin | Organizer: Keith Levin |
| B0724: S. Deshpande | |
| BART for network-linked data | |
| B0725: B. Betancourt | |
| A latent space model for multilayer network data | |
| B1278: L. Levina | |
| Latent space models for multiplex networks with shared structure | |
| B1337: D. Kessler, L. Levina | |
| Matrix-variate canonical correlation analysis with a network neuroscience application |
| Session EO136 | Room: 351 |
| Advances in statistical methods for medical data | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Michelle Miranda | Organizer: Michelle Miranda |
| B1285: N. Desai | |
| Covariance assisted multivariate penalized additive regression (ComPAdRe) | |
| B1865: J. Morris, Q. Cao, E. Sweeney, V. Baladandayuthapani, H. Yang, B. Renn | |
| Quantile functional regression for distributional regression of biomedical imaging data | |
| B1388: C. Beaulac | |
| Designing neural network layers for functional data analysis | |
| B1524: T. Ma, B. Risk | |
| A novel Bayesian covariance regression approach to unveil functional connectivity in resting-state fMRI data |
| Session EO133 | Room: 352 |
| New developments in high dimensional mixed effects and graphical models | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Yuedong Wang | Organizer: Yuedong Wang |
| Session EO167 | Room: 353 |
| Statistics in forensic science | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Jan Hannig | Organizer: Jan Hannig |
| B0238: M. Cuellar | |
| An algorithm for forensic toolmark comparisons | |
| B0291: K. Kafadar | |
| Estimating error rates in binary forensic decisions with inconclusive outcomes | |
| B0314: C. Saunders, J. Hanka, D. Ommen, J. Buscaglia | |
| Profile processes for approximate Bayesian computational model selection in forensic identification-of-source problems | |
| B0353: S. Lund, A. Pintar | |
| FICSing forensic footwear comparison |
| Session EO068 | Room: 354 |
| Statistical models for imbalanced datasets | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Marialuisa Restaino | Organizer: Marcella Niglio, Michele La Rocca, Marialuisa Restaino |
| B0581: S. Golia, M. Carpita | |
| A comparison of classifiers for multiclass classification models with imbalanced datasets | |
| B0787: R. Calabrese, Y. Dong, J. Zhang | |
| A novel generalized extreme value gradient boosting decision tree for the class imbalanced problem in credit scoring | |
| B1027: E. Ogundimu | |
| Variable selection in binary data with few events and possible separation | |
| B1354: K. Nadeem | |
| Stable variable ranking and selection in regularized logistic regression for severely imbalanced big binary data |
| Session EO321 | Room: 355 |
| New advances in statistical learning and simulation-based inference | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Haotian Xu | Organizer: Haotian Xu |
| B0310: R. Molinari, O.M. Romanus, Y. Boulaguiem, S. Guerrier | |
| Simulation-based differentially private inference for proportions | |
| B0598: Y. Zhang, S. Orso, M.-P. Victoria-Feser, S. Guerrier | |
| A computationally efficient framework for robust estimation | |
| B0644: S. Arya, B. Sriperumbudur | |
| Kernel epsilon-greedy strategy for contextual bandits | |
| B0867: S. Orso, M. Karemera, S. Guerrier, M.-P. Victoria-Feser | |
| Confidence intervals construction in complex parametric models facilitated by inconsistent estimators |
| Session EO239 | Room: 356 |
| Advances in optimal experimental design | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Sergio Pozuelo Campos | Organizer: Sergio Pozuelo Campos, Victor Casero-Alonso |
| B0240: I. Garcia-Camacha Gutierrez, K. Mylona | |
| A new Bayesian approach to control model misspecification in robust design | |
| B0473: K. Mylona | |
| Multi-objective optimal experimental split-plot designs for the industry: Case studies | |
| B0952: A. Munoz, V. Casero-Alonso, M. Amo-Salas | |
| Optimal experimental design applied to the Baranyi model | |
| B0998: S. Pozuelo Campos, V. Casero-Alonso, M. Amo-Salas | |
| Optimal designs for detecting and characterizing hormesis in toxicological tests |
| Session EO455 | Room: 357 |
| Advances in extreme value theory | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Zhongwei Zhang | Organizer: Zhongwei Zhang |
| B0244: J. Lederer | |
| High-dimensional extremes | |
| B1457: L. De Monte, I. Papastathopoulos, R. Campbell, H. Rue | |
| Multivariate extremes: Bayesian inference for radially-stable distributions | |
| B1662: O. Pasche, J. Zeder, S. Sippel, S. Engelke, E. Fischer | |
| The effect of a short observational record on the statistics of temperature extremes | |
| B1087: M. Krali, A. Davison, C. Klueppelberg | |
| Heavy-tailed max-linear structural equation models in networks with hidden nodes |
| Session EO288 | Room: 401 |
| Data heterogeneity and integration: Subgroups and individualized modeling | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Xiwei Tang | Organizer: Xiwei Tang |
| B0215: W. Zhou, L. Zhang, X. Tang, L. Wang | |
| Innovative unsupervised approach for simultaneous subgroup recovery and group-specific feature identification | |
| B1309: L. Tang | |
| RISE: robust individualized decision learning with sensitive variables | |
| B1310: S. Hyun, J. Bien, F. Ribalet | |
| Learning the ocean's microbial ecology using statistical mixture models | |
| B1962: H. Zhou, X. Tang | |
| Dynamic subgroup analysis on heterogeneous regression model |
| Session EO382 | Room: 403 |
| Statistical methods for high-dimensional and complex genomic data | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Mayetri Gupta | Organizer: Mayetri Gupta |
| B0252: L. Li, M. Gupta, V. Macaulay, I. Mukhopadhyay | |
| Bayesian group Lasso regression for genome-wide association studies | |
| B0307: M. Tadesse, M. Denis | |
| Bayesian graph-structured variable selection | |
| B0512: M. Evangelou | |
| Unsupervised learning approaches for multi-OMICS data | |
| B0522: Z. Qin | |
| Harnessing public genomics big data to gain functional insights on complex diseases |
| Session EO190 | Room: 404 |
| Advances in kernel methods and Gaussian processes | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Meng Li | Organizer: Meng Li |
| B0298: Z. Szabo, P. Bonnier, H. Oberhauser | |
| Kernel cumulants | |
| B1056: B. Sriperumbudur, O. Hagrass, B. Li | |
| Spectral regularized kernel two-sample test | |
| B1669: M. Li | |
| Optimal plug-in Gaussian processes for inferring functional derivatives and equivalence with kernel methods | |
| B1689: S. Banerjee, P. Alaimo Di Loro, M. Mingione, M. Jerrett, L. Jonah, Z. Daniel | |
| Process-based inference for accelerometer and streaming data from wearable devices |
| Session EO304 | Room: 414 |
| Recent advance in analytical methods for biomedical and clinical data | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Yi Zhao | Organizer: Yize Zhao |
| Session EO208 | Room: 424 |
| Applied directional statistics | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Guendalina Palmirotta | Organizer: Guendalina Palmirotta |
| B0468: O. Roenning | |
| Directional protein models as computer programs | |
| B0674: D. Marinucci | |
| Statistical analysis of spin random fields | |
| B0849: P. Jupp, R. Arnold | |
| Binary stars: uniformity, ambiguity and selection | |
| B1502: S. Loizidou, C. Ley, A. Anastasiou | |
| Optimal testing for symmetry on the torus |
| Session EO254 | Room: 442 |
| New perspectives in latent variable modeling II | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Cristina Mollica | Organizer: Maria Francesca Marino, Cristina Mollica |
| B1359: C. Galluccio, S. Bacci, B. Bertaccini, L. Grilli, C. Rampichini | |
| Considering latent evolving ability in test equating: Effects on final ranking and item parameter estimates | |
| B1444: Y. Melnykov, X. Zhu, V. Melnykov | |
| On contaminated transformation mixture models | |
| B1646: D. Henderson | |
| Mixtures of generalized Plackett-Luce models | |
| B1653: G. Capitoli, M.F. Marino, S. Galimberti, M. Lupparelli | |
| Latent space models for the hierarchical clustering of complex data in precision medicine |
| Session EO387 | Room: 444 |
| Societal implications of work in statistics and data science | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Jennifer Hill | Organizer: Ravi Shroff, Jennifer Hill |
| B1156: I. Lundberg | |
| The origins of unpredictability in life trajectory prediction tasks | |
| B1401: M. Baiocchi | |
| Challenging problems from the front lines of sexual assault prevention | |
| B1428: M. Coots | |
| Equity by design: Crafting algorithms for fair decision-making | |
| B1872: T. McCormick | |
| Prediction models, robustness, and decision-making |
| Session EO308 | Room: 445 |
| Statistical inference in modern observational studies | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Rajarshi Mukherjee | Organizer: Rajarshi Mukherjee |
| B1833: M. Azadkia | |
| On measures of dependence without model assumptions | |
| B1837: B. Karmakar, G. Mukherjee, W. Kar | |
| Penalized synthetic controls on truncated data with multiple treated and control units | |
| B1840: R. Nethery | |
| Causal exposure-response curve estimation with surrogate confounders: Air pollution epidemiology using Medicaid claims | |
| B1124: N. Laha, R. Mukherjee, B. Coull, N. Huey | |
| De-biased CCA: Theory and application |
| Session EO061 | Room: 446 |
| Causal inference for censored data (virtual) | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Erica Moodie | Organizer: Erica Moodie |
| B0172: J. Coulombe, E. Moodie, S. Shortreed | |
| Addressing longitudinal missing data to develop an individualized treatment rule for the choice of antidepressant drug | |
| B1148: R. Cook, A. Buhler, J. Lawless | |
| Considerations in defining estimands for clinical trials of complex disease processes | |
| B1149: K. Roysland | |
| Graphical criteria for the identification of causal effects in event-history analyses | |
| B1150: J. Young | |
| Causal inference with competing events |
| Session EO131 | Room: 447 |
| Random matrix theory for high-dimensional statistical problems | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Xiucai Ding | Organizer: Alexander Aue |
| B0871: N. Parolya, T. Bodnar | |
| Reviving pseudo-inverses: asymptotic properties of large dimensional generalized inverses with applications | |
| B1217: N. Doernemann, M. Lopes | |
| Tracy-Widom, Gaussian, and Bootstrap: Approximations for Leading Eigenvalues in High-Dimensional PCA | |
| B1269: A. Rohde | |
| Bootstrap of high-dimensional sample covariance matrices | |
| B1274: X. Ding | |
| Extreme eigenvalues of sample covariance matrices with generalized elliptical models with applications |
| Session EO274 | Room: 455 |
| Projection pursuit I | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Nicola Loperfido | Organizer: Nicola Loperfido |
| B0977: B. Ebner, J. Borodavka | |
| A general maximal projection approach to uniformity testing on the hypersphere | |
| B0549: Y. Duan, J. Cabrera | |
| Projection pursuit for big data | |
| B0660: D. Francom, G. Collins, K. Rumsey | |
| Bayesian projection pursuit regression | |
| B1979: S. Mukherjee | |
| Finite sample guarantees of projection pursuit |
| Session EO077 | Room: 457 |
| Advances in multivariate and high-dimensional statistics | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Joni Virta | Organizer: Joni Virta |
| B0492: A. Artemiou, C. Antonis | |
| Adaptive L0 approach for sparse quantile regression | |
| B0402: L. Heinonen, J. Virta | |
| A method for sparse independent component analysis | |
| B0701: J. Pere, B. Avelin, V. Garino, P. Ilmonen, L. Viitasaari | |
| Hill estimator and extreme quantile estimator for functionals of approximated stochastic processes | |
| B1417: K.-Y. Lee | |
| Functional structural equation model |
| Session EO232 | Room: Virtual R01 |
| New approaches for modeling high-dimensional multivariate data | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Wenbo Wu | Organizer: Wenbo Wu |
| B1841: W. Wu | |
| On partial envelop approach for modeling spatial-temporally dependent data | |
| B1842: X. Wang | |
| Clustering of longitudinal curves via a penalized method and EM algorithm | |
| B1862: T. Zu, Z. Zhao, Y. Yu | |
| FDR control for high dimensional quantile regression | |
| B1889: Z. Wei | |
| Recent development on stochastic frontier models |
| Session EO341 | Room: Virtual R02 |
| Advances in statistical and computational methods for omics data analysis | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Pei Wang | Organizer: Pei Wang |
| Session EO090 | Room: Virtual R04 |
| Advances on Bayesian methods for biostatistics and bioinformatics | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Marco Ferreira | Organizer: Marco Ferreira |
| B1264: S. Xu, J. Williams, M. Ferreira | |
| Iterative empirical Bayes for GWAS | |
| B1312: M. Ferreira, S. Xu, J. Williams | |
| Iterative Bayesian analysis of GLMMs for non-Gaussian GWAS data | |
| B1656: A. Tegge, M. Ferreira, H. Shin | |
| Bayesian clustering factor models | |
| B1275: H. Shin, M. Ferreira | |
| Dynamic ICAR spatiotemporal factor models |
| Parallel session F: CFE | Saturday 16.12.2023 | 17:10 - 18:50 |
| Session CI013 (Special Invited Session) | Room: 350 |
| Recent advances in structural VARs | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Joshua Chan | Organizer: Joshua Chan |
| A0410: H. Luetkepohl, M. Bruns | |
| Have the effects of shocks to oil price expectations changed? Evidence from heteroskedastic proxy vector autoregressions | |
| A0704: K.-L. Xu | |
| Local projection based inference under general conditions | |
| A0812: M. Lanne, J. Anttonen, J. Luoto | |
| Bayesian inference on fully and partially identified structural vector autoregressions |
| Session CO412 | Room: 227 |
| Complex network analysis in forecasting models | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Oleg Deev | Organizer: Oleg Deev, Stefan Lyocsa |
| A1028: S. Lyocsa, M. Stefanik, Z. Kostalova | |
| Forecasting online job vacancy attractiveness | |
| A1317: E. Baumohl, S. Lyocsa, T. Vyrost | |
| Threshold networks in credit risk models: An application on P2P markets | |
| A1592: O. Deev, T. Plihal, D. Sidlak | |
| Connected volatility: Global cross-asset network analysis of implied volatility | |
| A1183: Y. Liu, L.J. Baals, B. Hadji Misheva, J. Osterrieder | |
| Leveraging network topology for credit risk assessment in P2P lending |
| Session CO020 | Room: 236 |
| Time series econometrics | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Johan Lyhagen | Organizer: Johan Lyhagen |
| A0779: Y. Li, B.-G. Hansen, J. Lyhagen | |
| Identify the mean reverting properties and prediction of milk prices in EU countries | |
| A1166: V. Eriksson | |
| Modification index for ARMA models | |
| A1206: R. Sandberg | |
| Testing linearity in vector time-varying smooth transition autoregressive models when data are highly persistent | |
| A1652: Y. Yang, R. Sandberg, S. Ankargren | |
| Estimation and testing for multivariate nonlinearity of time series in the presence of additive outliers contamination |
| Session CO445 | Room: 256 |
| Financial computation and modeling | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Martina Zaharieva | Organizer: Martina Zaharieva |
| A0459: A. Virbickaite | |
| Structured factor copula models for modeling the default risk of European and U.S. banks | |
| A0703: A. Portela Santos, E. Ruiz, J. Frois Caldeira, W. Cordeiro | |
| Forecasting the yield curve:the role of time-varying decay parameters, conditional heteroscedasticity, and macro factors | |
| A0960: R. Lonn, A. Tetereva, C. Bemelmans | |
| Spanning the achievable stochastic discount factor with asset-pricing trees | |
| A1216: A. Kirilova, D. Muravyev, J. Hu | |
| Option market makers |
| Session CO021 | Room: 257 |
| Energy, sustainability and CO2 emissions | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Massimiliano Caporin | Organizer: Luigi Grossi, Massimiliano Caporin |
| A0814: G.L. Vriz, L. Grossi | |
| Green bubbles: A novel paradigm of detection and propagation | |
| A1857: M. Costola, K. Vozian | |
| Pricing climate transition risk: Evidence from European corporate CDS | |
| A1861: L. Grossi, M.S. Bernardi, A. Cerasa, F. Nan | |
| Outlier detection from auctions in electricity markets | |
| A0507: R. Yang | |
| Measuring the climate transition risk spillover |
| Session CO225 | Room: 258 |
| Machine learning in asset pricing | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Markus Pelger | Organizer: Markus Pelger |
| A0445: M. Weber, A. Neuhierl, J. Freyberger, B. Hoeppner | |
| Missing data in asset pricing panels | |
| A0484: V. Raponi, P. Zaffaroni | |
| Dissecting anomalies in conditional asset pricing | |
| A0635: D. Filipovic, P. Schneider, M. Multerer | |
| Kernel conditional density machines | |
| A1063: A. Tetereva, A. Quaini | |
| Economy-driven consumption-based asset pricing model |
| Session CO022 | Room: 259 |
| Modelling regime change and disruptions I | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Willi Semmler | Organizer: Willi Semmler |
| Session CO028 | Room: 260 |
| Bayesian time series methods for macroeconomics and finance | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: James Mitchell | Organizer: Gary Koop |
| A0853: J. Mitchell, T. Chernis, N. Hauzenberger, F. Huber, G. Koop | |
| Predictive density combination using a tree-based synthesis function | |
| A0897: N. Hauzenberger, F. Huber, G. Koop, J. Mitchell | |
| Bayesian modeling of TVP-VARs using regression trees | |
| A1091: D. Gefang | |
| Spike-and-slab group Dirichlet-Laplace priors for sparse shrinkages | |
| A1320: C. Li, Z. Zhang, R. Zhao | |
| Volatility or higher moments: which is more important in return density forecasts of stochastic volatility model? |
| Session CO395 | Room: 262 |
| Advances in factor models: Theory and application | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Antoine Djogbenou | Organizer: Antoine Djogbenou |
| A0190: S.H. Choi, D. Kim | |
| Large global volatility matrix analysis based on structural information | |
| A0198: A. Babii, E. Ghysels | |
| Tensor principal component analysis | |
| A0540: J. Goodhand | |
| Heterogeneous panel data models with generalized cross-section dependence | |
| A0600: F. Ayivodji | |
| Identification of common factors in group factor models | |
| A1902: A. Djogbenou | |
| Rolling window selection in FAR models with structural instabilities |
| Session CO279 | Room: 458 |
| HiTEc: Sustainable finance. Risk management and quantitative methods | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Sandra Paterlini | Organizer: Gabriele Torri, Sandra Paterlini |
| A0300: D. Nedela, T. Tichy, G. Torri | |
| Systemic risk detection using entropy approach in portfolio selection strategy | |
| A0699: R. Giacometti, G. Torri, K. Rujirarangsan, M. Cameletti | |
| Spatial multivariate GARCH models and financial spillovers | |
| A0913: G. Torri, R. Giacometti, J.M. Ricci | |
| Market implied ESG ratings | |
| A0691: S. Paterlini, K. Bax, G. Bonaccolto | |
| Spillovers in Europe: The role of ESG |
| Session CO327 | Room: Virtual R03 |
| Structural Models in IO | Saturday 16.12.2023 17:10 - 18:50 |
| Chair: Byoung Park | Organizer: Byoung Park |
| A1344: B. Park | |
| Time dependence and preference: Implications for compensation structure and shift scheduling | |
| A1345: M. Kim | |
| Backward compatibility in two-sided markets | |
| A1346: J. Yoon, Y. Shin | |
| Deposit market competition with entry and menu choice | |
| A1349: J. Lee, C.-Y. Ho, P. Chatterji | |
| Anti-competitive effects of common ownership in Medicare Part D |
| Parallel session G: CMStatistics | Sunday 17.12.2023 | 08:30 - 10:10 |
| Session EI009 (Special Invited Session) | Room: 350 |
| New contributions in extreme value analysis | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Armelle Guillou | Organizer: Armelle Guillou |
| B0157: C. Zhou, J. Einmahl | |
| Tail copula estimation for heteroscedastic extremes | |
| B0158: J. Einmahl, Y. He | |
| Extreme value inference for heterogeneous data | |
| B0159: A. Buecher, T. Jennessen | |
| Statistics for heteroscedastic time series extremes |
| Session EO194 | Room: 227 |
| Statistical modeling in management science | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Sujay Kumar Mukhoti | Organizer: Sujay Kumar Mukhoti |
| B0189: S. Ghosh, S. Mukhoti, P. Sharma, A. Banerjee | |
| Likelihood based estimation in three parameter beta distribution with application in critical inventory decision | |
| B0232: A. Banerjee, S. Mukhoti | |
| Rough-probabilistic modelling for demand specification | |
| B0268: K. Sriram | |
| Predicting the movement of anti state criminal gangs | |
| B0363: S.K. Mukhoti, A. Banerjee | |
| Asymmetric generalized newsvendor model |
| Session EO437 | Room: 335 |
| Dependence models for incomplete data | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Elif Acar | Organizer: Elif Acar |
| B0308: M. Delhelle, I. Van Keilegom | |
| Copula based dependent censoring in cure models | |
| B0413: P. Krupskiy, B. Nasri, B.N. Remillard | |
| On factor copula-based mixed regression models | |
| B0666: S. Abrams, P. Janssen, N. Veraverbeke | |
| Nonparametric estimation of quantiles of the conditional residual lifetime distribution | |
| B0946: W. He | |
| Identification of survival relevant genes with measurement error in gene expression incorporated |
| Session EO320 | Room: 340 |
| Clustering categorical and mixed-type data | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Cristina Tortora | Organizer: Cristina Tortora |
| B0392: G. Szepannek | |
| An overview on the clustMixType R package for clustering mixed-type data | |
| B0610: M. Nai Ruscone, D. Fernandez, K. Preedalikit, L. McMillan, I. Liu, R. Costilla | |
| One-dimensional mixture-based clustering for ordinal responses | |
| B1038: V. Melnykov, Y. Zhang | |
| On model-based clustering of multivariate categorical sequences | |
| B1101: A. Wilhelm, R. Aschenbruck, G. Szepannek | |
| Initialization strategies for clustering mixed-type data with the k-prototypes algorithm |
| Session EO297 | Room: 348 |
| Advances in multivariate and network time series methods | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Mirko Armillotta | Organizer: Mirko Armillotta |
| B0185: R. Adamek, I. Wilms, S. Smeekes | |
| Sparse high-dimensional vector autoregressive bootstrap | |
| B0188: A. Lee, G. Mesters, L. Hoesch | |
| Robust inference for non-Gaussian SVAR models | |
| B0267: G. Gudmundsson | |
| Detecting giver and receiver spillover groups in large vector autoregressions | |
| B0285: M. Armillotta, K. Fokianos | |
| Nonlinear network autoregression |
| Session EO135 | Room: 351 |
| Modern challenges in Bayesian inference | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Mario Beraha | Organizer: Mario Beraha, Federico Camerlenghi |
| B0349: A. Colombi, R. Argiento, F. Camerlenghi, L. Paci | |
| Mixture modeling via vector of normalized independent finite point processes | |
| B0572: B. Franzolini, B. Franzolini, A. Lijoi, I. Pruenster, G. Rebaudo | |
| Multivariate species sampling models | |
| B0958: J. Bryan | |
| Nonparametric estimation in the source apportionment problem | |
| B1070: D. Sulem, D. Rossell, J. Jewson | |
| Scalable Bayesian estimation of sparse Gaussian graphical models |
| Session EO145 | Room: 352 |
| Recent advances in space-time modelling (virtual) | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Maria Franco Villoria | Organizer: Maria Franco Villoria |
| B0915: L. Ferrari, M. Ventrucci, A. Laini | |
| Intuitive prior specification for spatiotemporal models in ecology | |
| B1011: M. Figueira Pereira, D. Conesa, A. Lopez-Quilez, I. Paradinas | |
| Modelling independent and preferential data jointly | |
| B1045: J. Paige, G.-A. Fuglstad, A. Riebler | |
| Accounting for geomasking in spatial modelling of complex survey data: A data fusion approach | |
| B1094: C. Zaccardi, P. Valentini, L. Ippoliti | |
| A novel approach for spatiotemporal confounding bias reduction |
| Session EO454 | Room: 353 |
| From data to wisdom | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Andriette Bekker | Organizer: Andriette Bekker |
| B0192: C. Ley, A. Groll, F. Felice, S. Bordas | |
| Statistically enhanced learning | |
| B0601: K. Burke | |
| Agent-based null models for examining experimental social interaction networks | |
| B0631: J. Ferreira, A. Bekker, A. Otto, A. Punzo, S.D. Tomarchio | |
| The inverted Dirichlet through a mode viewpoint with clustering applications | |
| B1380: M. Arashi | |
| Classification in high-dimension | |
| B1972: R. Mohammadi | |
| Large-scale Bayesian structure learning for gaussian graphical models using marginal pseudo-likelihood |
| Session EO065 | Room: 354 |
| Nonlinear models for time series | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Maddalena Cavicchioli | Organizer: Maddalena Cavicchioli |
| B0337: E. Kole, C. Brownlees | |
| High-dimensional dynamic factor models with Markov switching | |
| B0760: A. Beccarini | |
| Estimating a constrained regime-switching model by means of the EM-algorithm | |
| B0731: J. Cheng | |
| The importance of correct model specification: A regime switching GARCH MIDAS approach | |
| B0369: M. Cavicchioli | |
| Optimal forecasts for multivariate Markov switching autoregressive models |
| Session EO158 | Room: 356 |
| Design of experiments for big data | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Kalliopi Mylona | Organizer: Irene Garcia-Camacha Gutierrez, Kalliopi Mylona |
| B0301: V. Koutra | |
| Designing experiments on large networks | |
| B0494: C. Tommasi | |
| Unsupervised and supervised exchange-methods for subset selection from big datasets | |
| B1131: A. Molena, R. Fontana, L. Salmaso | |
| Combining design of experiments and machine learning in industrial experiments | |
| B1235: C. Drovandi | |
| A sequential experimental design approach for sub-setting big data |
| Session EO073 | Room: 401 |
| New developments in statistics for high frequency data | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Nakahiro Yoshida | Organizer: Nakahiro Yoshida |
| B0326: M. Uchida, Y. Tonaki, Y. Kaino | |
| Estimation for a linear parabolic SPDE in two space dimensions with a small noise based on high frequency data | |
| B0376: C. Mancini | |
| Drift burst test statistic in the presence of infinite variation jumps | |
| B0934: A. Gloter, C. Amorino, H. Halconruy | |
| Locally differentially private drift parameter estimation for iid paths of diffusion processes | |
| B0698: I. Muni Toke | |
| Neural network estimation of partially observed Hawkes processes |
| Session EO348 | Room: 403 |
| New developments in distance and depth-based statistical learning methods | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Silvia Salini | Organizer: Silvia Salini, Giancarlo Manzi |
| B0773: A. Grane Chavez, M. Riani, S. Salini | |
| A compared protocol to improve clustering procedures | |
| B0838: G. Manzi, A. Grane Chavez, M. Zanotti, Q. Guo | |
| Twitter sentiment analysis: Exploring users perceptions on health and well-being in Europe | |
| B0956: I. Cascos | |
| Strictly positive empirical expectile depth | |
| B1121: E. Boj, A. Grane Chavez | |
| Distance-based regression using robust Gower's distance |
| Session EO345 | Room: 404 |
| Statistical methods for sustainable practices | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Nicoletta D Angelo | Organizer: Nicoletta D Angelo, Giada Adelfio |
| B0181: P. Moraga | |
| Bayesian spatial modeling for data fusion adjusting for preferential sampling | |
| B0769: G. Loffredo, E. Romano, F. Maturo | |
| Random survival forest for functional data | |
| B0804: M. Eckardt | |
| Analyzing spatial point data with object-valued marks | |
| B0832: P. Maranzano, R. Borgoni, A. Tassan Mazzocco | |
| EEAaq: An R package to handle air quality data from the European environmental agency data portal |
| Session EO328 | Room: 414 |
| Recent developments in imaging and spatial statistics | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Veronica Berrocal | Organizer: Jian Kang |
| Session EO151 | Room: 442 |
| Recent advances in latent variable modeling | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Sara Taskinen | Organizer: Sara Taskinen |
| B0683: P. Korhonen, S. Taskinen, J. Niku, B. van der Veen, F. Hui | |
| Model-based ordination of multivariate vegetation percent cover data | |
| B0965: J. Kettunen, L. Mehtatalo, E.-S. Tuittila, A. Korrensalo, J. Vanhatalo | |
| Joint species distribution modeling with competition for space | |
| B0359: L. Guastadisegni, S. Cagnone, I. Moustaki, V. Vasdekis | |
| A novel test for detecting non-normality of the latent variable distribution with binary outcomes | |
| B0393: S. Tikka | |
| Bayesian modeling and causal inference for multivariate longitudinal data with R package dynamite |
| Session EO051 | Room: 444 |
| Orthogonalization and sparsity in neural networks | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: David Ruegamer | Organizer: David Ruegamer |
| B0783: M. Pfeuffer, R. Rane, K. Ritter, S. Greven | |
| Confounder control using semi-structured networks for neuroimaging data | |
| B0764: D. Koehler, D. Ruegamer, M. Schmid | |
| Functional decomposition through orthogonalization of neural additive models | |
| B0830: C. Kolb, B. Bischl, C.L. Mueller, D. Ruegamer | |
| Smoothing the edges: smooth optimization for sparse regularization using Hadamard overparametrization | |
| B0620: A. McInerney, K. Burke, D. Ruegamer | |
| Combining a smooth information criterion with neural networks |
| Session EO081 | Room: 445 |
| Advancement on causal mediation inference and related topics | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Wen Zhou | Organizer: Wen Zhou |
| B0587: K.C.G. Chan | |
| Mediation and partial conjunction testing via p-value spacings | |
| B0739: Y.S. Wang, M. Kolar, M. Drton | |
| Confidence sets for causal orderings | |
| B1369: Z. Liu | |
| DeepMed: Semiparametric causal mediation analysis with debiased deep learning | |
| B1583: A. McClean, Z. Branson, E. Kennedy | |
| Automatically Calibrated Sensitivity Models for Nonparametric Causal Inference with Unmeasured Confounding |
| Session EO425 | Room: 446 |
| Bayesian nonparametric and machine learning for causal inference | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Arman Oganisian | Organizer: Arman Oganisian |
| B0287: L. Hu | |
| Leveraging Bayesian ML for causal inference with missing longitudinal data | |
| B1039: A. Oganisian | |
| Bayesian semiparametric models for dynamic treatment rules with incomplete time-varying covariates | |
| B0819: M. Daniels, W. Bae | |
| A Bayesian non-parametric approach for causal mediation with a post-treatment confounder | |
| B0864: A. Canale, D. Zorzetto, F. Mealli, F.J. Bargagli Stoffi, F. Dominici | |
| Bayesian nonparametrics for principal stratification |
| Session EO403 | Room: 455 |
| Recent developments on networks and graphical models | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Arkaprava Roy | Organizer: Sayar Karmakar |
| B0810: D. Ganapathy, S. Deb, R. Roy | |
| Analyzing government health data to explore the COVID-19 management strategies | |
| B1356: A. Roy | |
| Graph estimation in high dimensional time-series | |
| B1692: S. Bhattacharya | |
| Inference and ranking in mixed-membership models | |
| B1921: S. Mukherjee | |
| Limit theorems and phase transitions in Tensor Curie-Weiss Ising and Potts Models |
| Session EO245 | Room: 457 |
| High-dimensional data analysis | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Johannes Lederer | Organizer: Johannes Lederer |
| B1276: A. Sabourin, S. Clemencon, N. Huet | |
| Regular variation in Hilbert spaces and principal component analysis for functional extremes | |
| B1482: A. Steland | |
| Online detection of changes in moment-based projections: When to retrain deep learners or update portfolios | |
| B1957: C. Durot | |
| Unlinked or shuffled monotone regression | |
| B1961: L.-X. Qin | |
| On data harmonization for tumor subtyping with microRNA data |
| Session EO161 | Room: 458 |
| HiTEc: Functional data clustering | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Mimi Zhang | Organizer: Mimi Zhang |
| B0796: M. Zhang, X. Zhao, E. Akeweje | |
| Ensemble clustering for learning mixtures of Gaussian processes | |
| B1214: F. Chamroukhi | |
| Learning mixtures-of-experts from heterogenous and high-dimensional data | |
| B1326: A. Torrente Orihuela, J. Albert Smet, J. Romo | |
| Band depth based initialization of k-means for functional data clustering | |
| B1333: F. Maturo, R. Verde, A. Porreca | |
| Enhancing performances in curves' classification: Learning from high-dimensional data via a two-step approach | |
| B1968: E. Romano, A. De Magistris, V. De Simone, G. Toraldo | |
| Free knot spline estimation with two roughness penalty terms for functional data and its application to clustering |
| Session EO529 | Room: Virtual R01 |
| Education and labor market: Applications and statistical advances | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Francesca Giambona | Organizer: Francesca Giambona |
| B0772: E. Fabrizi, A. Rocca | |
| The scarring effect of the NEET condition on young peoples future careers and the influence of the family background | |
| B0837: C. Usala, M. Porcu, I. Sulis | |
| Exploring the role of labor market conditions and university quality on university dropout | |
| B0963: A. Kahlawi, L. Buzzigoli, L. Grassini | |
| Dynamic skills demand in the Italian labor market: A comparative analysis of online job ads for 2019 and 2022 years | |
| B1032: A. Marletta, P. Mariani, P. Quatto | |
| Trajectory analysis for short time series in labor market: An application on European countries |
| B0803: I.-A. Moindjie, C. Preda | |
| Regression models with repeated functional data | |
| B1116: U. Mbaka, M. Carey | |
| Covariance matrix estimation for functional and longitudinal data | |
| B1129: T. Cardoso, M. Carey | |
| Complex surface reconstruction and its application in three-dimensional models of the human brain | |
| B0815: O. Kassi | |
| Learning the regularity of multivariate functional data |
| Session EC478 | Room: 355 |
| Machine learning | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Stathis Gennatas | Organizer: CFE-CMStatistics |
| B1384: Y. Liu | |
| Approximation of functions from Korobov spaces by shallow neural networks | |
| B1746: P. Bertail, S. Clemencon, Y. Guyonvarch, N. Noiry | |
| Empirical risk minimization in transductive transfer learning | |
| B1584: A. Okazaki, S. Kawano | |
| Multi-task learning regression based on convex clustering | |
| A1977: L. Fluri | |
| Feature importance for deep neural networks: A comparison of predictive power, infidelity, and sensitivity |
| Session EC532 | Room: 357 |
| Extreme values | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Stephane Girard | Organizer: CFE-CMStatistics |
| B1489: K. Herrmann, M. Hofert, J. Neslehova | |
| Morillas type transformations of stable tail dependence functions | |
| B1710: J. Holesovsky, M. Fusek | |
| Statistical inference for the local dependence condition in extreme value estimation | |
| B1570: Z. Zhang, D. Bolin, S. Engelke, R. Huser | |
| Extremal dependence of moving average processes driven by exponential-tailed Levy noise | |
| B1869: H. Lorenzo, S. Girard, J. Arbel | |
| Regularized partial least squares for extreme values |
| Session EC556 | Room: 424 |
| Computational and methodological statistics | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Dennis Dobler | Organizer: CFE-CMStatistics |
| B1967: I.I. Gauran, Z. Yu, H. Ombao | |
| Predictive performance test based on the exhaustive nested cross-validation for high-dimensional data | |
| B1975: A. Baillo, J. Carcamo, C. Mora-Corral | |
| Almost stochastic dominance hypothesis testing | |
| B1778: L. Kaufmann, M. Kateri | |
| Statistical inference for categorical covariates in high-dimensional logistic regression | |
| B1982: H. Zhang | |
| An innovative statistical method for co-localization in super-resolution microscope images |
| Parallel session G: CFE | Sunday 17.12.2023 | 08:30 - 10:10 |
| Session CO277 | Room: 236 |
| Time-varying dependence and structural change | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Liudas Giraitis | Organizer: Liudas Giraitis |
| A0466: J. Beran, J. Naescher, S. Walterspacher | |
| On Fourier based functional time series and state space models | |
| A0261: Y. Li, L. Giraitis, G. Kapetanios, T.C. Nguyen | |
| A partially time-varying regression model | |
| A0447: T. Terasvirta, A. Silvennoinen, J. Kang, C. He | |
| The North Atlantic Oscillation and monthly precipitation in selected European locations: A time series approach | |
| A0474: R. Kruse-Becher | |
| Adaptive now- and forecasting of global temperatures under smooth structural changes |
| Session CO195 | Room: 256 |
| Empirical econometrics with policy applications | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Christos Savva | Organizer: Christos Savva |
| A1495: C. Savva, D. Koursaros, K. Dimitriadis | |
| Does correlation of various commodities constitute reliable safe havens? | |
| A1468: D. Koursaros | |
| Financial literacy and advice: substitutes or complements? | |
| A1712: A. Stephan, P. Dahlstrom, H. Loof, M. Sahamkhadam | |
| Asset pricing of carbon emission disclosure |
| Session CO031 | Room: 258 |
| Topics in financial econometrics | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Leopold Soegner | Organizer: Leopold Soegner |
| A0860: M. Abdollahi, L. Soegner | |
| Monitoring cointegration in vector autoregressive models | |
| A0923: C. Oetjen | |
| Index insurance and catastrophe bonds for coping with agriculture risk in a multi-region setting | |
| A1034: R.A. Desenaldo, J. Sass | |
| Forecasting agricultural financial risk based on a linear index insurance model | |
| A1559: C. Haefke, L. Soegner | |
| Measuring systemic country risk |
| Session CO033 | Room: 259 |
| Modelling regime change and disruptions II | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Willi Semmler | Organizer: Willi Semmler |
| A0900: S. Wrzaczek, M. Kuhn, T. Upmann | |
| The value of information (VOI) in controlled dynamical environmental models with tipping points | |
| A1470: M. Coronese, F. Crippa, F. Lamperti, F. Chiaromonte, A. Roventini | |
| Raided by the storm: Impacts on income and wages from three decades of U.S. thunderstorms | |
| A1676: P. Chen | |
| Demand-pull or cost-push a Markov switching approach using Australian data | |
| A1709: I. Tahri | |
| Public infrastructure investment delays and transition risks |
| Session CO032 | Room: 260 |
| Applied macroeconomics I | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Michael Owyang | Organizer: Michael Owyang |
| A0245: M. McCracken, A. Amburgey | |
| Growth at risk is investment at risk | |
| A0246: A. De Polis, I. Petrella, L. Melosi | |
| The ever-changing challenges to price stability | |
| A0256: M. Faria-e-Castro | |
| A quantitative analysis of the countercyclical capital buffer | |
| A0798: M. Klein | |
| Estimating the effects of fiscal policy using a novel proxy shrinkage prior |
| Session CO428 | Room: 262 |
| Time series models for risk assessment and portfolio optimization | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Markus Haas | Organizer: Markus Haas |
| A0684: D. Umlandt | |
| Moment Conditions and Time-Varying Risk Premia | |
| A0228: M. Segnon | |
| Forecasting value-at-risk in time of ultra-high-frequency data | |
| A1106: M. Haas | |
| Regime-specific stock market behavior during the Covid-19 pandemic |
| Session CC523 | Room: 257 |
| Bayesian econometrics | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Toshiaki Watanabe | Organizer: CFE |
| A0417: J. Wroblewska, L. Kwiatkowski | |
| Identification of structural shocks in Bayesian VEC models with two-state Markov-switching heteroskedasticity | |
| A1635: Y. Kawakubo, K. Kakamu | |
| On estimating the decomposition of the income inequality measures | |
| A1731: M. Zaharieva, A. Virbickaite, A. Portela Santos | |
| Volatility transmission in global energy markets: A Bayesian nonparametric approach | |
| A1794: H. Nishino, K. Kakamu | |
| Bayesian model averaging for income distribution |
| Session CC538 | Room: 261 |
| Asset pricing and return predictability | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Ralf Wilke | Organizer: CFE |
| A1783: J. Bleher, T. Dimpfl, J. Grammig | |
| Comparing asset universes with expected shortfall frontiers constructed via quantile regression | |
| A0204: X. Yao, Z. Li, R. Hizmeri, M. Izzeldin | |
| Measuring downside option-implied correlation | |
| A1787: F. Schmidt, M. Demetrescu, R. Taylor | |
| Monitoring the predictability of stock returns under nonstationary volatility | |
| A1686: S. Kwok, R. Jarrow | |
| A study on asset price bubble dynamics: explosive trend or quadratic variation? |
| Session CC494 | Room: 447 |
| Computational and financial econometrics | Sunday 17.12.2023 08:30 - 10:10 |
| Chair: Tommaso Proietti | Organizer: CFE |
| B1992: J. Quelhas, A. Rua, N. Lourenco | |
| Navigating with a compass: Charting the course of underlying inflation | |
| A1994: J. Vecer | |
| Portfolio optimization without utility maximization with links to the frequentist and the bayesian statistics | |
| A1773: S. Koch, J. Bleher, T. Dimpfl | |
| Forecasting with Q: Density forecasts with local quantile projection and quantile vector autoregression | |
| A1978: H. Bonet Jaen, P. Angosto Fernandez, A. Perez Martin, M.V. Ferrandez-Serrano | |
| Analysis of abnormal returns through modified sharpe models: event study |
| Parallel session H: CMStatistics | Sunday 17.12.2023 | 10:40 - 12:20 |
| Session EV458 | Room: Virtual R01 |
| Time series and statistical models | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Gilles Stupfler | Organizer: CFE-CMStatistics |
| B0458: K.W. Chan, X. Liu | |
| No-lose converging kernel estimation of long-run variance | |
| B0805: T. Ito, S. Sugasawa | |
| Grouped generalized estimating equations for heterogeneous longitudinal data | |
| B1591: A. Baca, C. Bolance, R. Vernic | |
| On the bivariate Farlie-Gumbel-Morgenstern distribution with alternative composite exponential-Pareto marginals | |
| B1819: V. Hofer, G. Krempl, D. Lang | |
| An anticipative Bayesian stream classifier for data streams with verification latency |
| Session EO059 | Room: 335 |
| Statistical models for dependence II | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Elisa Perrone | Organizer: Elisa Perrone |
| B1690: O. Morales Napoles, M. t Hart, G. Torres-Alves, M.A. Mendoza-Lugo, E. Ragno, E. Perrone, P. Mares Nasarre | |
| Recent experiences with the use of Chimera for applications in statistics and engineering at the TU Delft | |
| B1644: J. Ansari, S. Fuchs | |
| A simple extension of Azadkia \& Chatterjee's rank correlation to a vector of endogenous variables | |
| B0881: T. Yoshiba, T. Koike, S. Kato | |
| On a measure of tail asymmetry for the bivariate skew-normal copula | |
| B1370: J.-L. Wermuth, M.-O. Pohle, T. Dimitriadis | |
| Measuring dependence between events |
| Session EO069 | Room: 340 |
| Mixed-type data clustering | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Cristina Tortora | Organizer: Cristina Tortora |
| B0602: J. Thompson, J. Ghashti | |
| Kernel metric learning for variable relevancy in mixed-type data clustering via maximum-similarity cross-validation | |
| B0767: M. van de Velden, A. Iodice D Enza, A. Markos, C. Cavicchia | |
| Mixed variables distances | |
| B1136: V. Veronesi, M. Markatou | |
| Measurement error and misclassification in clustering algorithms for mixed-type data |
| Session EO264 | Room: 348 |
| Multilayer and temporal network analysis | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Subhadeep Paul | Organizer: Subhadeep Paul |
| B0446: L. Leskela, K. Avrachenkov, M. Dreveton | |
| Community recovery from temporal and higher-order network interactions | |
| B0453: J. Loyal | |
| Fast variational inference for Bayesian nonparametric latent space models for dynamic networks using Bayesian P-Splines | |
| B0455: S. Paul | |
| Modeling temporal networks of relational events data | |
| B1908: D. Xia | |
| Optimal clustering in mixtures of multi-layer networks |
| Session EO196 | Room: 351 |
| Bayesian modeling for complex data | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Alessandro Colombi | Organizer: Lucia Paci |
| B0365: L. Ghilotti, F. Camerlenghi, T. Rigon | |
| Feature allocation models with EFPFs in product-form | |
| B0477: W. van den Boom, M. De Iorio, F. Qian, A. Guglielmi | |
| The multivariate Bernoulli detector: Change point detection in discrete survival analysis | |
| B0834: A. Avalos Pacheco, R. De Vito, B. Hansen | |
| Efficient integrative factor models: Applications from nutritional epidemiology to cancer genomics | |
| B1177: F. Castelletti, S. Peluso | |
| Bayesian learning of directed networks from interventional experimental data |
| Session EO258 | Room: 352 |
| Advances in Bayesian computational methods | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Khue-Dung Dang | Organizer: Khue-Dung Dang |
| B0746: N.M. Nguyen | |
| Particle Gaussian variational Bayesian | |
| B1062: S. Wei | |
| Real log canonical threshold: A complexity measure for deep neural networks | |
| B1581: R. Kohn, D. Gunawan, D. Nott | |
| Flexible variational Bayes-based on a copula of a mixture | |
| B0627: J. Arbel | |
| Rapture of the deep: Highs and lows of Bayes in a world of depths |
| Session EO201 | Room: 354 |
| Recent advances in goodness-of-fit testing and survival analysis | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Dimitrios Bagkavos | Organizer: Dimitrios Bagkavos |
| B0472: M.D. Jimenez-Gamero, M. Valdora, D. Rodriguez | |
| Testing homoscedasticity of a large number of populations | |
| B1110: B. Milosevic, Z. Lukic | |
| On the novel two-sample tests and their application for change point analysis | |
| B0296: R. Pelaez, R. Cao, J. Vilar Fernandez | |
| Smoothed Beran's estimator with bootstrap bandwidths: Application to COVID-19 hospital length-of-stay | |
| B1295: M. Kateri | |
| A longitudinal set-up for degradation modelling |
| Session EO357 | Room: 356 |
| Algebraic and geometric methods in doe | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Francesco Porro | Organizer: Fabio Rapallo, Francesco Porro |
| B0262: G. Pistone | |
| Information geometry of ANOVA and transport on a finite state space | |
| B0708: R. Fontana, M. Guerra | |
| Topological data analysis meets design of experiments: An exploration of 2-level non-isomorphic orthogonal arrays | |
| B0781: F. Porro, E. Riccomagno | |
| Algebraic statistics for data carrying relative, rather than absolute, information | |
| B1025: H. Maruri | |
| Sparse polynomial prediction |
| Session EO260 | Room: 357 |
| Extremes and risk | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Amir Khorrami Chokami | Organizer: Amir Khorrami Chokami |
| B0885: M. Brautigam, M. Kratz, M. Dacorogna | |
| A statistical approach to limit the effects of pro-cyclicality | |
| B1601: M. Kratz, J. Hambuckers, A. Usseglio-Carleve | |
| Efficient estimation for EV regression models of tail risks | |
| B1605: S. Aka | |
| Defining extreme droughts via run theory | |
| B0926: M. Dacorogna | |
| Building up cyber resilience by better grasping cyber risk via a new algorithm for modelling heavy-tailed data |
| Session EO184 | Room: 401 |
| Inference for stochastic differential equations | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Masayuki Uchida | Organizer: Masayuki Uchida |
| B0334: S. Kusano, M. Uchida | |
| Statistical inference in structural equation modeling with latent variables for diffusion processes | |
| B0569: H. Masuda, S. Eguchi | |
| Robustifying Gaussian quasi-likelihood inference | |
| B0681: N. Yoshida | |
| Asymptotic expansion for general Wiener functionals |
| Session EO388 | Room: 403 |
| Depth functions | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Thomas Laloe | Organizer: Thomas Laloe |
| B0335: S. Nagy | |
| Geometry and computation of halfspace depth for scatter matrices | |
| B0508: J.-B. Aubin, A. Rolland, E. Brun, S. Leoni, I. Gannaz | |
| An application of depth functions for social choice theory | |
| B0360: S. Armaut, T. Laloe, R. Diel | |
| A story of a functional depth through finite projections: An FPCA approach | |
| B0785: P. Berthet, J.-C. Fort | |
| Convergence of a bivariate quantile transform, contours and local depth |
| Session EO206 | Room: 404 |
| New advances in spatial econometrics | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Anna Gloria Bille | Organizer: Anna Gloria Bille |
| B0177: P. Caraiani | |
| Oil news shocks, inflation expectations and social connectedness | |
| B0361: S. Leorato, A. Martinelli | |
| Generalized spatial matrix specifications | |
| B1959: G. Millo | |
| Specifying spatial effects in panel data: Locally robust vs. conditional tests | |
| B1717: H. Tsukahara | |
| Spatial autoregressive models with copulas |
| Session EO039 | Room: 414 |
| Statistics in neuroscience I | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Russell Shinohara | Organizer: Russell Shinohara |
| B0219: S. Weinstein | |
| Network enrichment significance testing in brain-behavior association studies | |
| B0257: T. Johnson | |
| A Bayesian non-parametric Potts model for fMRI presurgical planning | |
| B0491: S. Simpson | |
| Regression frameworks for brain network distance metrics | |
| B1490: S. Lee | |
| Persistent homology-based functional connectivity measures for cognitive aging |
| Session EO252 | Room: 442 |
| New perspectives in latent variable modeling I | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Silvia Pandolfi | Organizer: Maria Francesca Marino |
| B0396: S. Bacci, B. Bertaccini, F. Cipollini | |
| Disentangling long term latent dynamics of the Brunelleschi's Dome cracks | |
| B0930: S. Giordano, R. Colombi | |
| Challenging the assumption of consistent responding behavior over time through a Markov switching model | |
| B1627: X. Qin, S. Dang, F. Martella | |
| Clustering via a finite mixture of disjoint factor analysis model | |
| B1663: I. Gollini | |
| A joint mixture model for the analysis of heterogeneous clusters in the alter group in interconnected ego-networks |
| Session EO052 | Room: 444 |
| Deep probabilistic models and interpretability | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: David Ruegamer | Organizer: David Ruegamer |
| B0753: M. Arpogaus | |
| Best of both worlds: Combining interpretable transformation models with the flexibility of normalizing flows | |
| B0947: P. Baumann | |
| Deep and interpretable probabilistic forecasts | |
| B0786: A. Thielmann, B. Saefken | |
| Neural additive models: Bridging the gap between interpretability and deep learning for enhanced predictive power |
| Session EO257 | Room: 446 |
| Trust in data science methods | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Markus Pauly | Organizer: Markus Pauly |
| B0352: S. Friedrich, A. Groll, K. Ickstadt, T. Kneib, M. Pauly, J. Rahnenfuehrer, T. Friede | |
| Regularization approaches in clinical biostatistics: A review of methods and their applications | |
| B1462: P. Doebler, M. Wischnewski, M. Beisemann, N. Kraemer | |
| Trust in automated systems as a multidimensional psychological construct | |
| B1391: G. Wunder | |
| How to provably generate privacy-preserving synthetic data for the data economy | |
| B1387: C. Schlauch, C. Wirth, N. Klein | |
| Bayesian methods for informing trajectory predictions in safe autonomous driving |
| Session EO100 | Room: 447 |
| Advances in functional and object data analysis | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Sonja Greven | Organizer: Sonja Greven |
| B1738: L. Sangalli, E. Arnone, L. Clementi, A. Palummo, H.A. Hernandez, M.C. Aguilera-Morillo, R. Lillo | |
| Functional data analysis over multidimensional non-Euclidean domains | |
| B1086: A. Stoecker, L. Steyer, S. Greven | |
| Functional additive models for forms of plane curves and their visualization | |
| B0509: J.M. Jeon, G. Van Bever | |
| Additive regression with general imperfect variables | |
| B1068: S. Greven, L. Steyer | |
| Principal component analysis in Bayes spaces for sparsely sampled density functions |
| Session EO070 | Room: 455 |
| Some challenges for multivariate statistics | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Nicola Loperfido | Organizer: Nicola Loperfido |
| B0374: M. Kelner, U. Makov, Z. Landsman | |
| A novel methodology to expand the Archimedean copula parameters: Application to peak demand estimation | |
| B0657: G. McLachlan | |
| Learning of classifiers from partially classified training data | |
| B0534: Z. Landsman, U. Makov | |
| On the minimum variance squared regression | |
| B0433: T. Shushi, N. Loperfido | |
| The theory of optimal portfolio projections and their applications |
| Session EO334 | Room: 457 |
| Regularized methods for statistical inference | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Peter Craigmile | Organizer: Peter Craigmile, Christopher Hans |
| B0686: D. Kunkel, M. Peruggia | |
| Statistical inference with anchored Bayesian mixture of regressions models | |
| B0825: C. Hans, N. Liu | |
| Sampling the Bayesian elastic net | |
| B0862: M. Peruggia, E. Kim, S. MacEachern | |
| Regularized empirical likelihood for Bayesian inference: Theory and applications | |
| B0869: P. Craigmile, S. Tang, Y. Zhu | |
| Spectral analysis using multitaper Whittle methods with a Lasso penalty |
| Session EO446 | Room: Virtual R02 |
| Measurement and missing data in causal inference for mHealth | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Linda Valeri | Organizer: Linda Valeri |
| Session EC545 | Room: 227 |
| Statistics for economics and finance | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Svetlana Makarova | Organizer: CFE-CMStatistics |
| B1623: H. Mahamat | |
| Simultaneous estimates of the beta of the market line with generalized autoregressive conditional heteroscedastic errors | |
| B1941: M. Olszak, S. Roszkowska, C. Godlewski | |
| Macroprudential policy, governance, openness and finance and loan loss provisions of European banks | |
| B1733: P. Luitel, M. Doan, P. Sercu, T. Vinaimont | |
| Efficient Y-indices for regressions with an application of Covid's impact on stock-market liquidity | |
| B1745: M. Jaeger-Ambrozewicz | |
| Comparing duration vectors |
| Session EC485 | Room: 353 |
| Applied statistics | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Philipp Otto | Organizer: CFE-CMStatistics |
| B0730: C. Keribin, R. Coulaud, G. Stoltz | |
| Probabilistic modelling of passenger movements to predict onboard loads | |
| B1446: N. Ouachene, C. Czado, T. Senga Kiesse, M. Corson | |
| R-vines as a new way to model interactions within French dairy-cattle systems | |
| B1799: M. Stachova, J. Hunady | |
| Using a two-step clustering approach to examine courts' efficiency in European countries | |
| B1850: D. Li, W.K. HUI, X. Fan | |
| Bayesian inhomogeneous hidden Markov model with incomplete observations and its application to EHR modelling |
| Session EC541 | Room: 355 |
| Variable selection | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Roman Hornung | Organizer: CFE-CMStatistics |
| B1251: I. Barrio, A. Iparragirre, T. Lumley, I. Arostegui | |
| On Lasso regression for complex survey data: A new replicate weights cross-validation proposal | |
| B1436: S. Tanaka, H. Matsui | |
| Variable screening using factor analysis for high-dimensional data with multicollinearity | |
| B1730: F. Kizilaslan, D.M. Swanson, V. Vitelli | |
| Classical and Bayesian approaches for the mixture cure model with high-dimensional covariates | |
| B1981: Y. Huang, S. Pirenne, S. Panigrahi, G. Claeskens | |
| Selective inference using randomized group lasso estimators with general loss functions |
| Session EC544 | Room: 424 |
| Semiparametric regression | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Keisuke Yano | Organizer: CFE-CMStatistics |
| B1435: N. Pya Arnqvist, P. Arnqvist | |
| Expanding the boundaries of generalized additive modelling with shape constraints in R | |
| B1481: J. Lichter, T. Kneib | |
| Variational inference for locally shape constrained splines | |
| B1615: G. Callegher, T. Kneib, P. Wiemann, J. Soeding | |
| Stochastic variationally inference for multivariate latent gaussian models | |
| B1660: S. Skhosana, S. Millard, F. Kanfer | |
| A new approach to estimate semi-parametric Gaussian mixtures of non-parametric regressions |
| Session EC474 | Room: 445 |
| Computational and methodological statistics II | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Pier Giovanni Bissiri | Organizer: CFE-CMStatistics |
| B1980: B. Monroy-Castillo, M.A. Jacome Pumar, R. Cao | |
| Improved distance correlation estimation | |
| B1993: M. Castro, L. Hernandez-Velasco, C. Abanto-Valle, D. Dey, M. Castro | |
| A Bayesian approach for mixed effects state-space models under skewness and heavy tails | |
| B2001: M. Khismatullina | |
| Clustering of multivariate nonparametric time trends | |
| B1836: T. Besbeas | |
| Unified methodology for observation- and parameter-driven models for time series |
| Parallel session H: CFE | Sunday 17.12.2023 | 10:40 - 12:20 |
| Session CI317 (Special Invited Session) | Room: 350 |
| Volatility, intensity and jumps | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Carsten Chong | Organizer: Carsten Chong |
| A0168: M. Rosenbaum, G. Szymanski | |
| From no-arbitrage to rough volatility via market impact | |
| A0169: M. Hoffmann | |
| A statistical theory for rough volatility inference | |
| A0167: C. Chong, V. Todorov | |
| A nonparametric rough volatility test |
| Session CO226 | Room: 236 |
| Time series models for large systems of variables | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Esther Ruiz | Organizer: Esther Ruiz |
| A0528: C. Lissona, M. Barigozzi | |
| Measuring the Euro area output gap(s): A large-dimensional dynamic factor model approach | |
| A0529: E. Ruiz, D. Fresoli, P. Poncela | |
| Prediction intervals for common factors in dynamic factor models with cross-correlated idiosyncratic components | |
| A1073: A. Giovannelli, T. Proietti, A. Cerasa, F. Nan | |
| Quantifying uncertainty in electricity prices forecasting: Models and methods | |
| A0776: C. Doz, L. Ferrara, P.-A. PIONNIER | |
| Business cycle dynamics after the Great Recession: An extended Markov-switching dynamic factor model |
| Session CO062 | Room: 256 |
| Machine learning in finance | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Anastasija Tetereva | Organizer: Anastasija Tetereva |
| A0535: M.T. Phan, M. Fengler | |
| A topic model for 10-K management disclosures | |
| A0503: J. Schuettler, F. Audrino, F. Sigrist | |
| Investor sentiment and the cross section of stock returns: A natural language processing approach | |
| A0912: H. Ma | |
| Extract investor sentiment from price disparity via model-based neural networks | |
| A1069: J. Llorens-Terrazas | |
| An oracle inequality for multivariate dynamic quantile forecasting |
| Session CO338 | Room: 257 |
| Household finance using SHARE data | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Andrej Srakar | Organizer: Giacomo Pasini, Andrej Srakar |
| Session CO291 | Room: 259 |
| Advances in financial econometrics | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Emese Lazar | Organizer: Emese Lazar, Genaro Sucarrat |
| A0633: S. Campos Martins, R. Engle | |
| A two-factor model of sovereign bond volatilities | |
| A0677: F. Violante, S. Grassi | |
| Generalized autoregressive conditional betas | |
| A1620: E. Lazar, S. Wang, J. Pan | |
| Environmental performance and credit ratings: A transatlantic study | |
| A1942: E.-C. Brinkop, E. Lazar, M. Prokopczuk | |
| Deep learning with time contextual data |
| Session CO106 | Room: 260 |
| Applied macroeconomics II | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Michael Owyang | Organizer: Michael Owyang |
| A0250: A. Rogantini Picco, L. Melosi, F. Zanetti, H. Morita | |
| The signaling effects of fiscal announcements | |
| A0313: C. Otrok | |
| The evolution of global inflation pre and post pandemic | |
| A0826: M. Owyang | |
| Are treasury BEIs inflation expectations? |
| Session CO153 | Room: 261 |
| Advances in Bayesian financial econometrics | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Toshiaki Watanabe | Organizer: Toshiaki Watanabe |
| Session CO023 | Room: 262 |
| Advances in high-dimensional structural modeling | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Martin Wagner | Organizer: Martin Wagner |
| A0590: L. Soegner, M. Wagner | |
| Open-end monitoring of structural breaks in the cointegration VAR | |
| A1288: K. Kidik, D. Bauer | |
| Identification of autoregressive models for matrix valued time series with multiple terms | |
| A1289: D. Bauer | |
| Using subspace algorithms to estimate the factor dynamics in generalized dynamic factor models | |
| A1292: A. Konstantopoulos, C. Zwatz, M. Wagner | |
| GVAR models and linear transformations of VAR processes |
| Session CO016 | Room: 458 |
| HiTEc: Advances in forecasting and risk management | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Alessandra Amendola | Organizer: Alessandra Amendola |
| A0483: N. Nolde | |
| Stress scenario estimation with vine copulas | |
| A0695: A. Amendola, V. Candila, A. Naimoli, G. Storti | |
| Adaptive combinations of tail-risk forecasts | |
| A1118: J. Andersson, D. Karlis | |
| Forecasting with and maximum likelihood estimation of the vector autoregressive to anything (VARTA) model | |
| A1705: C. Schult, K. Heinisch, F. Scaramello | |
| Advancing forecast accuracy analysis: A partial linear instrumental variable and double machine learning approach |
| Session CC536 | Room: 258 |
| Causal inference | Sunday 17.12.2023 10:40 - 12:20 |
| Chair: Maddalena Cavicchioli | Organizer: CFE |
| A0357: E. Lopetuso | |
| Causal analysis of cointegrated systems: Model manifestations of hierarchical properties | |
| A0490: J. Ruzicka | |
| Quantile structural vector autoregression | |
| A1697: H. Liao, X. Wang | |
| Causal effects on volatility by causal-GARCH model | |
| A1785: M. Martinoli, A. Moneta, G. Pallante | |
| Calibration and validation of macroeconomic simulation models by statistical causal search |
| Parallel session I: CMStatistics | Sunday 17.12.2023 | 13:50 - 15:30 |
| Session EO424 | Room: 227 |
| Statistical analysis of complex data and its applications | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Lyudmila Sakhanenko | Organizer: Nilanjan Chakraborty |
| B0435: T. Masak, K. Waghmare, V. Panaretos | |
| The functional graphical lasso | |
| B0451: B.C. Boniece, L. Horvath, L. Trapani | |
| On distributional change-point detection in functional time series | |
| B0384: M. Wheelock | |
| Network-level analysis for connectome-wide association studies | |
| B0397: L. Sakhanenko, N. Chakraborty, D. Zhu | |
| Novel bootstrap tests for parametric structures of high dimensional covariances |
| Session EO110 | Room: 259 |
| Statistical modeling for complex data and DiD approaches | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Abdul-Nasah Soale | Organizer: Abdul-Nasah Soale, Andrej Srakar |
| B0790: E. Tsyawo, G. Koumou | |
| DiD with as few as two cross-sectional units: An application to the impact of democracy on growth | |
| A1451: C. Park, E. Tchetgen Tchetgen | |
| A universal difference-in-differences approach for causal inference | |
| A1574: N. Seewald, B. McGinty, K. Tormohlen, I. Schmid, E. Stuart | |
| Handling correlation in stacked difference-in-differences estimates with application to medical cannabis policy | |
| B0713: A.-N. Soale | |
| Dimension reduction and data visualization for regression with metric valued response |
| Session EO359 | Room: 335 |
| Recent progress in robust causal inference | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Ziwei Mei | Organizer: Zijian Guo |
| B1727: Y. Zhang | |
| Adjustment with many regressors under covariate-adaptive randomizations | |
| B1832: C. Shi | |
| On the assumptions and misspecifications of synthetic controls | |
| B1839: Z. Mei, Q. Fan, Z. Guo, C.-H. Zhang | |
| Uniform Inference for Nonlinear Endogenous Treatment Effects with High-Dimensional Covariates | |
| B1844: N. Apfel | |
| Detecting grouped local average treatment effects and selecting true instruments |
| Session EO299 | Room: 340 |
| Clustering three-way data | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Nicola Loperfido | Organizer: Nicola Loperfido |
| B0592: P. McNicholas | |
| Clustering three-way data | |
| B0595: M. Neal, P. McNicholas | |
| Variable selection for clustering of three-way data | |
| B0632: A. Sochaniwsky, P. McNicholas | |
| Tolerance values for stopping rules | |
| B0710: K. Clark, P. McNicholas | |
| Trimming outliers in matrix-variate normal mixtures using the OCLUST algorithm |
| Session EO233 | Room: 348 |
| Advances in network data analysis | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Jesus Arroyo | Organizer: Jesus Arroyo |
| B1281: L. Cappello, S. Walker | |
| Recursive estimation of probability distributions | |
| B0423: I. Bhattacharya, A. Ertefaie, K. Lynch, J. McKay, B. Johnson | |
| Nonparametric Bayesian Q-learning for optimization of dynamic treatment regimes in the presence of partial compliance | |
| B0541: M. Giordano | |
| Bayesian nonparametric intensity estimation for inhomogeneous point processes with covariates | |
| B1175: T. Randrianarisoa, B. Szabo | |
| Variational Gaussian processes for linear inverse problems |
| Session EO276 | Room: 352 |
| Recent advances for complex data analysis | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Juan Romo | Organizer: Juan Romo |
| B1911: R. Lillo, B. Pulido Bravo, A. Franco-Pereira | |
| Clustering functional data with the aid of epigraph and hypograph indexes: the journey | |
| B1914: A.M. Paganoni, F. Ieva, J. Romo | |
| A Spearman dependence matrix for multivariate functional data | |
| B1923: J.L. Torrecilla, C. Ramos Carreno, A. Suarez | |
| A recursive approach to variable selection with functional data | |
| B1928: A. Justel, M. Svarc, G. Liniers, P. Sanz, S. Gonzalez | |
| Advanced statistical tools to compare HYSPLIT air parcel trajectories in the Artic and Antarctic regions |
| Session EO418 | Room: 353 |
| Statistical machine learning with kernels and nonlinear transformations | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Wenkai Xu | Organizer: Wenkai Xu |
| B1527: P. Mozharovskyi, M. Matabuena, R. Ghosal, O.H. Madrid Padilla, J.-P. Onnela | |
| Conditional conformal depth measures algorithm for uncertainty quantification in complex regression models | |
| B1671: N. Rivera, T. Fernandez, W. Xu | |
| New resampling schemes for composite goodness-of-fit tests with kernels | |
| B1952: W. Xu, J. Yang | |
| Learning and testing heavy-tail distribution via stereographic projection |
| Session EO217 | Room: 354 |
| Charting the course through coarsened data | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Sarah Lotspeich | Organizer: Tanya Garcia, Sarah Lotspeich |
| B0229: I. Van Keilegom | |
| Estimation of the density for censored and contaminated data | |
| B0531: G. Tarr, I. Wilms | |
| Aggregating noisy data for improved prediction in multiclass models | |
| B0499: B. Baer | |
| A coarsened data perspective of counterfactual survival analysis | |
| B1040: P. Shaw, B. Shepherd, J. Yang, T. Lumley | |
| Efficient validation designs to support error-corrected analyses of EHR data |
| Session EO079 | Room: 355 |
| Machine learning and biostatistical methods for health data science | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Liqun Diao | Organizer: Liqun Diao |
| Session EO199 | Room: 357 |
| Recent advances in statistical modeling for risk management | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Olivier Lopez | Organizer: Olivier Lopez |
| B0591: O. Laverny | |
| Copulas.jl: Implementation of standard copula routines in Julia | |
| B0770: M. Thomas | |
| Parametric insurance for extreme risks: The challenge of properly covering severe claims | |
| B0799: J. Legrand, T. Opitz, M. Oesting, P. Naveau | |
| Extreme events and climate risks |
| Session EO072 | Room: 401 |
| Empirical measures and smoothing methods | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Eric Beutner | Organizer: Henryk Zaehle, Eric Beutner |
| B1378: B. Klar, A. Hanebeck | |
| Smooth distribution function estimation for lifetime distributions using Szasz-Mirakyan operators | |
| B1859: E. Beutner, H. Zaehle | |
| New concentration inequalities for classical and smoothed empirical processes | |
| B1936: S. Sun Mitchell | |
| Asymptotic normality of the deconvolution kernel density estimator based on strong mixing and right censored data | |
| B1938: Z. Goldfeld | |
| Gromov-Wasserstein alignment: Statistical and computational advancements via duality |
| Session EO071 | Room: 403 |
| Recent developments on data depth and applications | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Sara Lopez Pintado | Organizer: Sara Lopez Pintado, Alicia Nieto-Reyes |
| B0721: Y. Fu, X. Shi, Y. Zhang | |
| Two-sample tests based on data depth | |
| B1624: H. Yeon, X. Dai, S. Lopez Pintado | |
| A new statistical depth for functional data | |
| B1742: S. Lopez Pintado, D. Lopez-Pintado, I. Garcia Milan, Z. Yao | |
| Uncertainty analysis of contagion processes based on a functional depth approach | |
| B1954: A. Castellanos, P. Mozharovskyi, F. d Alche-Buc, H. Janati | |
| Kernel-based extension of the halfspace depth |
| Session EO043 | Room: 404 |
| Statistics and machine learning in multi-omics data analysis and beyond | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Roman Hornung | Organizer: Roman Hornung |
| B1483: F. Buettner | |
| Uncertainty quantification in multi-omics data analysis and beyond | |
| B1090: D. Wissel, N. Janakarajan, A. Grover, E. Toniato, M. Rodriguez Martinez, V. Boeva | |
| SurvBoard: Standardized benchmarking for cancer survival models | |
| B1659: M. Wuensch, C. Sauer, L.C. Hinske, A.-L. Boulesteix | |
| Over-optimism in gene set analysis: How do the choices made by the researcher influence the results? | |
| B0981: R. Hornung, F. Ludwigs, J. Hagenberg, A.-L. Boulesteix | |
| Prediction approaches for partly missing multi-omics covariate data: An overview and an empirical comparison study |
| Session EO040 | Room: 414 |
| Statistics in neuroscience II | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Jeff Goldsmith | Organizer: Jeff Goldsmith |
| B0227: E. Hector | |
| Distributed model building and recursive integration for functional connectivity modeling | |
| B1030: A. Mejia | |
| Rethinking artifact removal in functional MRI from a statistical perspective | |
| B0556: S. Vandekar, K. Kang, J. Seidlitz, J. Schildcrout, R. Tao, A. Alexander-Bloch, J. Xiong, M. Jones, R. Bethlehem | |
| Effect sizes and replicability in brain-wide association studies | |
| B0720: J. Wrobel, J. Goldsmith | |
| Modeling trajectories using functional first-order linear differential equations |
| Session EO243 | Room: 424 |
| Statistical innovation in pharmaceuticals | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Chenguang Wang | Organizer: Chenguang Wang |
| B0659: Z. Wang, G. Rosner, C. Wang | |
| Biomarker adaptive two-stage design for Phase II targeted therapy | |
| B1233: C. Wang | |
| Leveraging real world data and real world evidence in clinical trial design and analysis and its causal implications | |
| B1684: S. Roychoudhury | |
| Dynamic enrichment of small sample, sequential, multiple assignment randomized trial (snSMART) design | |
| B1762: S. Bae | |
| Adaptive strategies for clinical trial design |
| Session EO350 | Room: 442 |
| Advances in latent variable modeling with complex data structure | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Silvia Bacci | Organizer: Silvia Bacci |
| B0664: M. Battauz, G. Alfonzetti, R. Bellio | |
| A competing risk latent variable model for the analysis of university students' careers | |
| B0818: L. Bungaro, B. Veldkamp, M. Matteucci, S. Mignani | |
| Cheaters' detection via response times in computerized adaptive testing | |
| B1229: S. Pandolfi, F. Bartolucci, F. Pennoni | |
| Maximum likelihood inference for hidden Markov models with parsimonious parametrizations of transition matrices | |
| B1306: M. Iannario | |
| A new framework for jointly modelling response times and accuracy in computer-based learning tests |
| Session EO047 | Room: 444 |
| Measuring fairness, explainability and safety of machine learning models | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Emanuela Raffinetti | Organizer: Emanuela Raffinetti |
| B0989: N. Golini, L. Patelli, R. Ignaccolo, M. Cameletti | |
| Explaining spatial regression random forest | |
| B1608: V. Ghidini | |
| Statistics and explainability, an ideal partnership | |
| B0239: G. Babaei, P. Giudici | |
| How fair is machine learning in credit scoring? | |
| B0950: C. Muckley | |
| Detecting dementia: Money management difficulty and flagging early stage dementia in financial data |
| Session EO300 | Room: 445 |
| Concentration and conformal prediction | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Arun Kuchibhotla | Organizer: Arun Kuchibhotla |
| B1219: R. Farina, A. Kuchibhotla, E. Tchetgen Tchetgen | |
| Conformal prediction for survival data | |
| B1226: H. Bong, A. Kuchibhotla | |
| Tight concentration inequality for sub-Weibull random variables with variance constraints | |
| B1256: K. Scharfstein, A. Kuchibhotla | |
| Time-uniform conformal and probably approximately correct prediction | |
| B1257: S. Sarkar, A. Kuchibhotla | |
| Asymptotic inference for the mean with minimal assumptions |
| Session EO313 | Room: 446 |
| Methodological advances in statistical translation of omics and EHR data | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Li-Xuan Qin | Organizer: Li-Xuan Qin |
| B0178: J. Wang, P. Huang, M. Cai, C. McKennan | |
| Accurate estimation of rare cell type fractions from tissue omics data via hierarchical deconvolution | |
| B1100: A. Ni, L.-X. Qin | |
| Batch effect correction in microRNA-seq data for survival risk prediction | |
| B1112: D. Scholtens | |
| Network models for multi-omics data | |
| B1348: J. Chen | |
| A constrained maximum likelihood approach to developing well-calibrated risk prediction models |
| Session EO097 | Room: 447 |
| Recent developments on dimension reduction and functional data analysis | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Eliana Christou | Organizer: Eliana Christou |
| B0469: C.E. Lee, X. Zhang, L. Li | |
| Dimension reduction for tensor response regression models | |
| B0807: S. Wang, V. Patilea | |
| Adaptive functional scores | |
| B0982: C. Capezza, F. Centofanti, D. Forcina, A. Lepore, B. Palumbo | |
| Control charts for functional data based on functional mixture regression | |
| B1019: J. Di Iorio, N.A. Lazar | |
| Triclustering algorithm for functional data with a focus on fMRI data |
| Session EO406 | Room: 457 |
| Robust estimation for contemporary data | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Jing Zhou | Organizer: Jing Zhou |
| B0283: I. Kalogridis | |
| Robust and adaptive functional logistic regression | |
| B0292: Z. Zhang, R. Li, X. Yu | |
| A novel approach of high dimensional linear hypothesis testing problem | |
| B0302: M. Li, Y. Yu, T. Wang, Y. Chen | |
| Robust mean change point testing in high-dimensional data with heavy tails | |
| B0712: C. Li, J. Zhou | |
| Unconditional treatment effect with high-dimensional covariates and unmeasured confounding |
| Session EO198 | Room: 458 |
| HiTEc: Contributions to the analysis of high-dimensional and complex data | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Eugen Pircalabelu | Organizer: Eugen Pircalabelu |
| B1279: A. Munteanu, S. Omlor, D. Woodruff | |
| Sketching for logistic regression | |
| B1409: K. Knight | |
| An adaptive weighted mean for multivariate location estimation | |
| B1552: X. Bing | |
| Optimal vintage factor analysis with deflation varimax | |
| B1573: K. Waghmare, V. Panaretos | |
| Continuously indexed graphical models |
| Session EO210 | Room: Virtual R01 |
| Recent advances in causal inference and data analysis | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Widemberg da Silva Nobre | Organizer: Widemberg da Silva Nobre |
| B0439: X. Qin, L. Wang | |
| Causal moderated mediation analysis: A causal investigation of heterogeneity in mediation mechanisms | |
| B0444: M.-A. Bind, D. Rubin | |
| Counternull sets in randomized experiments | |
| B0964: K. Rudolph, I. Diaz, N. Williams | |
| Causal mediation with instrumental variables | |
| B1173: T. Nguyen | |
| Sensitivity analysis for principal ignorability violation in estimating complier and noncomplier average causal effects |
| Session EO342 | Room: Virtual R02 |
| Recent advances in causal inference and its application | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Yuexia Zhang | Organizer: Yuexia Zhang |
| B0420: Q. Zhang, Z. Yang, J. Yang | |
| Mediation analysis with high dimensional exposures or confounders | |
| B1105: K. Li, E. Tchetgen Tchetgen | |
| A two-stage-least-square approach for negative control of unmeasured confounding with time-to-event outcomes | |
| B1232: X. Zhang, L. Wang, S. Volgushev, D. Kong | |
| Fighting noise with noise: Causal inference with many candidate instruments | |
| B0339: Y. Zhang, A. Qu, Y. Yuan, Q. Xu, F. Xue, K. Wei | |
| Exploring the causal relationship between Geriatric depression and Alzheimer's disease |
| Session EO221 | Room: Virtual R03 |
| Methods for spatial transcriptomic data | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Farouk Nathoo | Organizer: Farouk Nathoo |
| Session EO456 | Room: Virtual R04 |
| Recent developments in theory and applications of robust learning | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Yunlong Feng | Organizer: Yunlong Feng |
| Session EC479 | Room: 356 |
| Design of experiments | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Kalliopi Mylona | Organizer: CFE-CMStatistics |
| B0274: T. Dasgupta | |
| Design and analysis of audits experiments | |
| B0942: R. Chowdhury, N.S. Upadhye | |
| A novel improvement acquisition function | |
| B1494: S. Horii | |
| Bayesian sequential experimental design for Gaussian-process-based partially linear model | |
| B0220: D. Ferreira, S. Ferreira | |
| Optimizing allocation rules: A novel approach for estimating confidence ellipsoids and minimizing allocation costs |
| Session EC471 | Room: 455 |
| Biostatistics | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Antoine Usseglio-Carleve | Organizer: CFE-CMStatistics |
| Parallel session I: CFE | Sunday 17.12.2023 | 13:50 - 15:30 |
| Session CI012 (Special Invited Session) | Room: 350 |
| Advanced machine learning methods in finance | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Christina Erlwein-Sayer | Organizer: Christina Erlwein-Sayer |
| A0214: R. Korn | |
| Modelling and portfolio optimization with sustainable assets | |
| A0236: N. Packham | |
| Risk factor detection with methods from explainable ML | |
| A0571: P. Schwendner | |
| Case studies of primary and secondary market dynamics |
| Session CO024 | Room: 236 |
| Recent developments in time series and panel econometrics | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Robinson Kruse-Becher | Organizer: Robinson Kruse-Becher |
| A0536: A. Mayer, M. Massmann | |
| Least squares estimation in nonlinear cohort panels with learning from experience | |
| A0576: T. Hartl | |
| The fractional unobserved components model | |
| A0797: M. Hosseinkouchack, M. Demetrescu | |
| Detecting the predictive power of imperfect predictors with slowly varying components | |
| A1159: N. Salish, M. Salish | |
| Saving for sunny days: The impact of climate change on consumer prices in the euro area |
| Session CO112 | Room: 256 |
| Session on inflation and inflation expectations | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Galina Potjagailo | Organizer: Saeed Zaman |
| A0371: A. Allayioti, F. Monti, M. Piffer | |
| The transmission of monetary policy when agents fear extreme inflation outcomes | |
| A1895: B. Meyer | |
| What we are learning about firms' inflation expectations | |
| A0331: S. Zaman, J. Mitchell | |
| The distributional predictive content of inflation expectations measures | |
| A0409: G. Potjagailo, C. Griffa | |
| Determinants of firms pricing in the UK - expectations and industry-level complementarities |
| Session CO176 | Room: 257 |
| Modelling financial markets | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Menelaos Karanasos | Organizer: Menelaos Karanasos |
| A1798: S. Yfanti, M. Karanasos, J. Wu | |
| The short- and long-run cyclical variation of the cross-asset nexus | |
| A1808: J. Wu, M. Karanasos | |
| Spillover effect in financial market via a bivariate component model | |
| A1831: Y. Karavias, M. Barassi, C. Zhu | |
| Threshold regression in heterogeneous panel data with interactive fixed effects | |
| A1797: M. Realdon | |
| New discrete time affine models to price sovereign credit risk |
| Session CO400 | Room: 258 |
| Economic diversification, energy transition and the environment | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Peter Pedroni | Organizer: Fakhri Hasanov, Peter Pedroni |
| A0520: D. Hendry | |
| Econometric forecasting of climate change | |
| A1528: N. Ericsson | |
| Labor force participation and unemployment: Structural change from the pandemic | |
| A1964: F. Hasanov, P. Pedroni | |
| Model averaging: A case study of the petrochemical sector in a large-scale general equilibrium macro model | |
| A1943: P. Pedroni, F. Hasanov | |
| Economic diversification through renewable energy and the role of FDI |
| Session CO336 | Room: 260 |
| Topics in financial macroeconomics | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Christian Proano | Organizer: Christian Proano |
| A1352: L. Mateane | |
| Measuring the impact of aggregate demand shocks on Germany's trade balance and industry using Bayesian SVARs | |
| A1367: L. Quero Virla, C. Proano, T. Strohsal | |
| How strong is the link between the global financial cycle and regional macro-financial dynamics? A wavelet analysis | |
| A1330: N. Kotb, C. Proano | |
| Monetary policy, stock prices and temporal aggregation in a new Keynesian model with behavioral expectations | |
| A1884: C. Proano, P. Engler, L. Draeger, L. Mateane | |
| How do borrower- and Lender-based macroprudential policies affect the transmission mechanism of fiscal policy? |
| Session CO197 | Room: 261 |
| Recent advances in Bayesian time-series estimation and forecasting | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Pawel Szerszen | Organizer: Mohammad Jahan-Parvar |
| A1324: P. Szerszen, C. Knipp, M. Jahan-Parvar | |
| Bayesian trend-cycle decomposition and forecasting | |
| A1476: G. Amisano | |
| The term structure of natural rates of interest | |
| A1512: B. Siliverstovs | |
| Bayesian multiple-indicator mixed-frequency model with moving average stochastic volatility | |
| A0194: N. Chen | |
| Bayesian value at risk forecast using CARE model with an application of cryptocurrency |
| Session CO228 | Room: 262 |
| High complexity time series models | Sunday 17.12.2023 13:50 - 15:30 |
| Chair: Anindya Roy | Organizer: Anindya Roy |
| A1691: V. Pipiras | |
| Multivariate time series modeling for multiple subjects | |
| A1751: S. Basu | |
| Impulse response estimation in large-scale time series | |
| A1769: T. Nguyen | |
| Probabilistic forecast for time series with transformer-based models | |
| A1725: A. Roy | |
| Bayesian graph estimation under causal vector autoregressive time series |
| Parallel session J: CMStatistics | Sunday 17.12.2023 | 16:00 - 18:05 |
| Session EI011 (Special Invited Session) | Room: 458 |
| HiTEc: Measure transportation and multivariate quantiles | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Marc Hallin | Organizer: Marc Hallin |
| B0155: T. Verdebout | |
| Measure-transportation-based quantiles and ranks for directional data | |
| B0156: G. Mordant, M. Hallin | |
| Measure-transportation-based Lorenz curves and concentration indices | |
| B1616: E. del Barrio, A. Gonzalez-Sanz, M. Hallin | |
| Nonparametric measure-transportation-based multiple-output quantile regression |
| Session EO223 | Room: 227 |
| High-dimensional and non-parametric inference for time series | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Anne Leucht | Organizer: Anne Leucht, Jens-Peter Kreiss |
| B0184: X. Shao, H. Gao, R. Wang | |
| Dimension-agnostic change point testing | |
| B1125: M. Duker | |
| Testing for common structures in high-dimensional factor models | |
| B1503: S. Richter, W.B. Wu, J. Li, Z. Lou | |
| Asymptotic theory for constant step size stochastic gradient descent | |
| B0317: N. Neumeyer | |
| Generalized Hadamard differentiability of the copula mapping and its applications in time series models | |
| B0774: E. Paparoditis | |
| Periodogram bootstrap |
| Session EO351 | Room: 256 |
| Advanced statistical modelling for artificial intelligence and finance | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Maria Iannario | Organizer: Codruta Mare, Maria Iannario |
| B0941: C. Tarantola, S. Facchinetti, M. Iannario, S.A. Osmetti | |
| Enhancing cyber risk assessment: Unfolding ordinal data models for effective analysis | |
| B1366: C. Breitung, G. Kruthof, S. Mueller | |
| The context: Determining sentiment using large language models | |
| B1786: L. Stanca, C. Dabija | |
| Navigating the retail landscape: Understanding customer behavior during the COVID-19 pandemic and its impact on finance | |
| B1881: B. Bedowska-Sojka, J. Gorka | |
| Do uncertainty indices affect cryptocurrency uncertainty: A lesson from turbulent times | |
| B1910: S. Belbe, D.-G. Susanu, A. Vulpe | |
| Information extraction using transformers |
| Session EO526 | Room: 335 |
| Individualized treatment strategies and treatment effect heterogeneity | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Nicholas Illenberger | Organizer: Nicholas Illenberger |
| B0378: K. Linn, J. Shen, R. Hubbard | |
| Estimation and evaluation of individualized treatment rules following multiple imputation | |
| B0407: E. Moodie, D. Stephens, A. Turchetta | |
| New approaches to design and monitoring of SMARTs | |
| B0599: D. Spicker, E. Moodie, S. Shortreed | |
| Preserving patient privacy in dynamic treatment regimes: Private outcome-weighted learning (PrOWL) | |
| B0847: H. Park | |
| A simple approach to modeling pre- vs post-treatment differences in functional connectivity | |
| B1008: Y. Zhao | |
| Estimating optimal tailored active surveillance strategy under interval censoring |
| Session EO089 | Room: 340 |
| Computational Methods for Large-Scale Data Analysis | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Yixuan Qiu | Organizer: Yixuan Qiu |
| B1415: J. Wang | |
| Heritability estimation with similarity decoding | |
| B1423: J. Kim | |
| Generative AI for model selection | |
| B1425: H. Chun | |
| saVAE for nonlinear dimension reduction | |
| B1480: H. Cheng, Y. Chen, P. Ma, W. Zhong | |
| Graphon cross-validation | |
| B1523: P. Breheny | |
| Penalized mixed models to adjust for batch effects and unobserved confounding in high dimensional regression |
| Session EO323 | Room: 348 |
| Recent advances in random networks | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Robert Lunde | Organizer: Monika Bhattacharjee |
| B0344: S.K. Kar, N.T. Argon, S. Bhamidi, S. Ziya | |
| A generalized influence maximization problem | |
| B0375: A. Acharyya, J. Agterberg, M. Trosset, Y. Park, C. Priebe | |
| Convergence guarantees for response prediction in latent structure networks on unknown one-dimensional manifolds | |
| B0381: D. Wang, C. Misael Madrid, O. Hernan Madrid | |
| Trend filtering for temporal-spatial models | |
| B0440: R. Lunde | |
| On the validity of conformal prediction for network data under non-uniform sampling |
| Session EO048 | Room: 350 |
| Sports analytics | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Christophe Ley | Organizer: Andreas Groll, Christophe Ley |
| B0199: M. Maricic, M. Ignjatovic, V. Uskokovic | |
| Application of statistics in sport related research: A bibliometric analysis | |
| B0460: R. Bajons, K. Hornik | |
| Curve clustering methods and their applications to sports analytics | |
| B0757: G. Calvo, C. Armero, L. Spezia | |
| Can we model the hot hand phenomenon? A Bayesian hidden Markov approach for assessing basketball team performance | |
| B0763: J. Renteria, L. Zumeta-Olaskoaga, E. Bikandi, J. Larruskain, D.-J. Lee | |
| Identification of injury risk factors for professional football players: A multivariate survival tree approach | |
| B1486: F. Felice, C. Ley | |
| Predicting handball games with machine learning and teams strengths statistics |
| Session EO215 | Room: 351 |
| Bayesian modeling of time-series data | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Michele Guindani | Organizer: Michele Guindani |
| B0808: F. Bassetti, R. Casarin, M. Iacopini | |
| Time varying autoregressive gamma shot noise model for wildfires | |
| B0895: S. Peluso, S. Chib, A. Mira | |
| A Bayesian change-point analysis of vector autoregressive processes | |
| B1171: P. Knaus, S. Fruehwirth-Schnatter | |
| Effective dynamic shrinkage via the dynamic triple gamma prior | |
| B1198: A. Giampino, M. Guindani, B. Nipoti, M. Vannucci | |
| Changepoint detection with random partition models | |
| B1915: R. Casarin | |
| Bayesian dynamic calibration of models predictions |
| Session EO442 | Room: 352 |
| Advances in statistical models and methods for complex data analysis | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Jacopo Di Iorio | Organizer: Jacopo Di Iorio |
| B0577: M. Cremona, L. Doroshenko, F. Severino | |
| Functional motif discovery in stock market prices | |
| B0629: E. Arnone, L. Clementi, L. Sangalli | |
| Analyzing data in complex 3D domains: Smoothing, semiparametric regression and functional principal component analysis | |
| B1003: F. Michelis | |
| Nonnegative matrix factorization with induced sparsity on inverse covariance matrix | |
| B1071: N. Sapargali, C. Fritz, B. Sischka, G. Kauermann | |
| Accounting for network dependencies when assessing covariate effects via graphon random effect | |
| B1082: F. Centofanti, A. Lepore, B. Palumbo | |
| Sparse and smooth clustering of functional data |
| Session EO157 | Room: 353 |
| Statistical learning of non-Gaussian data | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Xianzheng Huang | Organizer: Xianzheng Huang |
| B0284: T. Nagler | |
| Stationary vine copula models for count data | |
| B0461: T. Wang | |
| Measurement error modeling on zero-inflated and overdispersed microbiome sequence count data | |
| B0791: Y. Li | |
| Statistical inference for Cox proportional hazards models with a diverging number of covariates | |
| B0890: S. Shimizu | |
| Non-Gaussian methods for causal discovery | |
| B0992: Q. Liu, D. Bandyopadhyay, D. Pati | |
| A semiparametric single index model with non-Gaussian residuals for quantifying periodontal disease |
| Session EO244 | Room: 355 |
| Semiparametric and nonparametric methods in mental health research | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Andrew Chen | Organizer: Andrew Chen |
| B0640: A. Li, R. Perry, C. Huynh, J. Vogelstein | |
| Manifold random forests for decoding EEG data and estimating mutual information | |
| B0658: J. Liu | |
| Evaluating latent structures in the graphical network model: visual exploration and hypothesis testing | |
| B0865: P. Reiss, B. Paul | |
| A continuous-time distributed lag model for experience sampling data | |
| B1050: T. Ogden, S. Xie | |
| Functional support vector machine | |
| B1107: H. Shou | |
| Two-sample test for multivariate activity densities evaluated from wearable devices over repeated assessments |
| Session EO162 | Room: 356 |
| Statistical learning: Privacy, robustness and policy making | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Yufei Zhang | Organizer: Chengchun Shi |
| B0195: L. Wang | |
| Optimizing the dynamic personalized health care decision rules when clinical restrictions exist | |
| B0277: G. Yin, J. Gu | |
| Hierarchical and stochastic crystallization learning with Delaunay triangulation | |
| B0893: T. Berrett, Y. Yu, M. Li | |
| On robustness and local differential privacy | |
| B1049: D. Rothenhaeusler, K. Bansak, E. Paulson | |
| Random distribution shift in refugee placement: Strategies for building robust models | |
| B1108: Y. Zhang, E. Neuman, W. Stockinger | |
| Offline learning for price impact models |
| Session EO202 | Room: 357 |
| Multivariate peaks-over-threshold in high dimensions | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Thomas Opitz | Organizer: Thomas Opitz |
| B0761: F. Reinbott, A. Janssen, M. Schlather | |
| Max-stable principal component analysis and its properties | |
| B0784: F. Roettger, J. Coons, A. Grosdos | |
| Colored graphical models in multivariate extremes | |
| B1133: M. Oesting, J. Lederer | |
| Extremes in high dimensions: Methods and scalable algorithms | |
| B1189: M. Hentschel, S. Engelke, J. Segers | |
| Statistical inference for Huesler-Reiss graphical models through matrix completions | |
| B0619: A. Mourahib, J. Segers, A. Kiriliouk | |
| Multivariate generalized Pareto distributions along extreme directions |
| Session EO121 | Room: 401 |
| Bayesian asymptotics (virtual) | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Catia Scricciolo | Organizer: Catia Scricciolo |
| B1009: A. Bhattacharya | |
| On the convergence of coordinate ascent variational inference | |
| B0320: B. Ning | |
| Empirical Bayes large-scale multiple testing for high-dimensional sparse binary sequences | |
| B0706: A. Norets | |
| Locally robust efficient Bayesian inference | |
| B0380: T. Pan, W. Shen, G. Hu | |
| Bi-directional clustering via averaged mixture of finite mixtures | |
| B0351: D. Pati | |
| Adaptive finite element type decomposition of Gaussian random fields |
| Session EO306 | Room: 403 |
| Over-parametrization and overfitting in machine learning | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Debarghya Ghoshdastidar | Organizer: Debarghya Ghoshdastidar |
| B1283: M. Murray | |
| Mildly over-parameterized shallow ReLU networks: Favorable loss landscapes and benign overfitting | |
| B0955: A. Derumigny, J. Schmidt-Hieber | |
| On lower bounds for the bias-variance trade-off | |
| B1042: K. Donhauser | |
| Strong inductive biases provably prevent harmless interpolation | |
| B1199: L. Chennuru Vankadara | |
| Is memorization compatible with causal learning: The case of high-dimensional linear regression | |
| B1920: C. Mayrink Verdun, J. Maly, H. Mirandola, H.-H. Chou | |
| An overparametrized point of view on nonnegative regression |
| Session EO067 | Room: 404 |
| Developments in spatial and spatio-temporal disease modeling | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Andrew Lawson | Organizer: Andrew Lawson |
| B0846: A. Lawson, Y. Xin | |
| Bayesian age decomposition modeling of Covid-19 space-time dynamics | |
| B0935: T. Neyens, A. Rozo Posada, A. Janssens, C. Faes, P. Libin, J. Crevecoeur | |
| Spatiotemporally modelling opportunistically sampled epidemiological data: pitfalls and solutions | |
| B0971: D. Lee | |
| Computationally efficient localized spatial smoothing of disease rates using anisotropic basis functions | |
| B1060: H. Quick, J. Kwon | |
| Multivariate spatial modeling for producing age-standardized rate estimates for small areas | |
| B1098: H. Baptista | |
| Similarity- and neighborhood-based dynamic models |
| Session EO137 | Room: 414 |
| Advances in analyzing complex data | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Hossein Moradi Rekabdarkolaee | Organizer: Hossein Moradi Rekabdarkolaee |
| B0225: M.K. Shirani Faradonbeh | |
| Online data-driven decision-making in unknown continuous environments | |
| B0237: E. Boone | |
| Uncertainty quantification for fractional partial differential equations with unknown forcing functions | |
| B0275: S.Y. Samadi, R. Ibrahim, T.P. De Alwis | |
| Spatiotemporal high-dimensional matrix autoregressive models via tensor decomposition | |
| B0605: T. Hansen | |
| Model-free approaches to state estimation and control of electric power grids using emerging machine learning techniques | |
| B1322: L. Shand, G. Huerta | |
| A multivariate space-time dynamic model for characterizing downstream impacts of geoengineering events |
| Session EO256 | Room: 424 |
| Novel 'omics methods: Transcriptomics, microbiome, and metabolomics | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Siyuan Ma | Organizer: Siyuan Ma, Jonathan Schildcrout |
| B1595: R. Deek | |
| Statistical and computational methods for integrating microbiome and host omics data | |
| B1919: P. Basak, H. Mallick, A. Porwal, S. Saha, V. Svetnik, E. Paul | |
| An integrated Bayesian framework for multi-omics prediction and classification | |
| B1932: A. Bhattacharyya | |
| A two-part Tweedie model for differential analysis of omics data | |
| B1935: S. Ma | |
| Compositional differential abundance analysis for health-microbiome associations and controlling false discoveries | |
| B1976: A. Rahnavard | |
| deepBreaks: A machine learning tool for identifying and prioritizing genotype-phenotype associations |
| Session EO118 | Room: 442 |
| Modern methods and computational techniques for multifaced data | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Tsung-I Lin | Organizer: Luis Mauricio Castro, Tsung-I Lin |
| B0550: W.-L. Wang, T.-I. Lin | |
| Extending multivariate nonlinear mixed models with censored and non-ignorable missing outcomes | |
| B0997: F. Schumacher, K. Zhong, V.H. Lachos Davila | |
| Bayesian scale mixture of normal censored linear mixed models with within-subject serial dependence | |
| B1057: F. Louzada | |
| On a generalized closed-form maximum likelihood estimator for some survival distributions | |
| B0476: M. Prates, L. Michelin, L. Godoy | |
| Fast mixture spatial regression: A mixture in the geographical and feature space applied to predict oil in the post-salt | |
| B1443: R. Vallejos, F. Osorio, C. Ferrer | |
| A coefficient to measure agreement between two continuous variables based on a L1 norm |
| Session EO207 | Room: 444 |
| Explainability in machine learning | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Natalia Golini | Organizer: Natalia Golini, Rosaria Ignaccolo |
| B0222: E. Raffinetti, P. Giudici | |
| A new proposal to assess robustness of artificial intelligence methods | |
| B0894: M. Setzu | |
| Explainable AI: Empowering machine learning models with explanations | |
| B0545: B. Yu | |
| Interpreting deep neural networks towards trustworthy AI | |
| B0816: C. Iorio, M. Aria, A. Gnasso, G. Pandolfo | |
| Unlocking explainable in ensemble trees | |
| B0929: C. Vens | |
| Building random forest explanations through a locally accurate rule extractor |
| Session EO383 | Room: 445 |
| Recent developments in complex survival analysis | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Chi Hyun Lee | Organizer: Chi Hyun Lee |
| B0263: W. Li, J. Ning, J. Zhang, Z. Li, S. Savitz, A. Tahanan, M. Rahbar | |
| Enhancing long-term survival prediction with multiple short-term events | |
| B1685: S.H. Chiou, Y. Sun, C. Wu, M. McGarry, C. Huang | |
| Dynamic risk prediction triggered by intermediate events using survival tree ensembles | |
| B0622: D. Alvares, S. Roumpanis, F. Mercier, S. Yiu, V. Shah, F. Castro, J. Barrett, Y. Zhu | |
| A two-stage approach for joint modelling of competing risks and multiple longitudinal outcomes | |
| B0986: S. Kang, J.-Y. Park, B. Seo, J. Kim | |
| Accelerated failure time modeling with time-dependent covariates via nonparametric Gaussian scale mixtures | |
| B1397: J. Qian, E. Parner, M. Overgaard, R. Betensky | |
| Pseudo-observation regression for sequentially truncated data |
| Session EO224 | Room: 446 |
| Applied statistical and psychometrics issues in measurement | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Daphna Harel | Organizer: Klint Kanopka, Daphna Harel |
| B0305: D. Harel | |
| Effect size measures for differential item functioning | |
| B0408: A. Alvero | |
| ChatGPT is people: Comparing synthetic and human-made text across social dimensions | |
| B0411: K. Gorney, S. Sinharay, C. Eckerly | |
| Efficient corrections for standardized person-fit statistics | |
| B0496: S. Student | |
| Empirical tests of the assumptions underlying growth measurement in vertical scaling | |
| B0654: K. Kanopka, B. Domingue | |
| Projecting the performance of polytomous item response models onto a common scale with the InterModel Vigorish |
| Session EO075 | Room: 447 |
| Novel statistical methods for wearable device data | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Jaroslaw Harezlak | Organizer: Jaroslaw Harezlak |
| B1578: L. Natarajan, R. Zablocki | |
| Measurement and analysis of sedentary behavior derived from wearable sensors | |
| B1579: M. Yu, Z. Wu, M. Hicken, M. Elliott | |
| A Bayesian approach for modeling variance of intensive longitudinal Biomarker data as a predictor of health outcomes | |
| B1630: Q. Cao | |
| Detection of medication taking using wrist-worn commercially available wearable device | |
| B1858: C. Tekwe | |
| Functional multiple indicators, multiple causes measurement error models |
| Session EO530 | Room: 455 |
| Computational statistics for environment and life | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Ayesha Ali | Organizer: Ayesha Ali |
| B0304: R. Ghanam | |
| SEIRD model for Qatar: A case study | |
| B0330: D. Ankerst | |
| Globally-accessible and individual-tailored clinical risk prediction | |
| B0497: G. Chiu, A.C. Hyman, R. Lipcius | |
| A state space approach to modeling the influence of seagrass availability on juvenile blue crab population dynamics | |
| B1267: A. Cooper, A. Ali, Z. Feng | |
| Analysis of compositional benthic data via regularized Dirichlet-multinomial regression | |
| B1419: A. Bhullar, K. Nadeem, A. Ali | |
| Where should we grow them? Deep learning for agricultural management in Canada |
| Session EO095 | Room: 457 |
| Massive or high dimensional data: Sketching, subsampling, and more | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Alexander Munteanu | Organizer: Alexander Munteanu |
| B0290: M. Lopes, J. Yao, B. Erichson | |
| Error estimation for random Fourier features | |
| B0625: H.C. Lie | |
| Error analysis of random subsampling methods for Bayesian inference | |
| B0647: T. Campbell | |
| Bayesian coresets | |
| B1805: Z. Ding | |
| Efficiency coresets techniques with multivariate conditional transformation models | |
| B1088: M. Mutny | |
| Challenges of experiment design in high-dimensional spaces |
| Session EO117 | Room: Virtual R01 |
| Causal LLM, digital health, efficient training, kinlessness, M\&As | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Roy Welsch | Organizer: Roy Welsch |
| B1752: M. Pittavino, B. Arpino, E. Pirani | |
| Estimating ageing kinlessness across Europe | |
| B1755: R.-I. Cobzaru, R. Welsch, S. Finkelstein, Z. Shahn | |
| Using large language models for variable selection in observational healthcare studies | |
| B1818: J. Zou | |
| The impact of M\&As on financial innovation | |
| B1753: H. Xie | |
| A stochastic sampling method to enable efficient training | |
| B1925: A. AlShehhi | |
| Digital health for Parkinson's disease (PD) diagnose and assessment |
| Session EO152 | Room: Virtual R03 |
| New developments in robust statistics | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Conceicao Amado | Organizer: Ana Maria Bianco, Graciela Boente |
| B0255: E. Cabana Garceran del Vall, R. Lillo | |
| Robust shrinkage-based methods | |
| B0259: A. Garcia-Perez | |
| The robust inverse-dispersion weighted estimator in Mendelian randomization | |
| B0269: M. Ruiz, G. Lafit, F.J. Nogales, R. Zamar | |
| Robust and sparse estimation of Gaussian graphical models based on Winsorization | |
| B0346: M. Souto de Miranda, M.C. Miranda, C. Amado, I. Gomes | |
| A study on extremal index robust estimation considering it like a proportion | |
| B0857: K. Nordhausen, D. Tyler, M. Yi | |
| Robust and resistant regularized covariance matrices |
| Session EO371 | Room: Virtual R04 |
| Advances in modeling time series of complex data structures | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Scott Bruce | Organizer: Scott Bruce |
| B1520: S. Yun | |
| Multiple testing for spatial extreme with application to climate model evaluation | |
| B1876: P. Bagchi | |
| Detection of structural breaks in non-stationary spatial random field | |
| B1875: S. Bruce, Z. Li, T. Cai | |
| Interpretable classification of categorical time series using the spectral envelope and optimal scalings | |
| B1887: R. Sundararajan | |
| Student-t stochastic volatility model with composite likelihood EM-algorithm |
| Session EP002 | Room: Poster Virtual Room 1 |
| Poster Session I | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Cristian Gatu | Organizer: CFE-CMStatistics |
| B1252: X. Su | |
| Zero-inflated Bayesian hierarchical mixture model to address the missing data and dropouts for scRNA-Seq data | |
| B1619: I. Ortega-Fernandez, M. Sestelo | |
| Explainable generalized additive neural networks with independent neural network training | |
| B1776: J. Gutierrez-Botella, M. Pata, C. Armero, T. Kneib, F. Gude | |
| Studying heart failure progression through Bayesian multi-state survival models | |
| B1792: M. Del Angel, M. Nunes, D. Thompson | |
| Unlocking the potential of wearable data: Time series analysis for comprehensive understanding of physical activity | |
| B1883: G. Carere, H.C. Lie | |
| Low-rank posterior approximations for linear Gaussian inverse problems on separable Hilbert spaces | |
| B1913: E. Costa, I. Papatsouma | |
| A novel approach to outlier detection for mixed-type data | |
| B1464: R. Caballero-Aguila, J. Linares-Perez | |
| Quadratic filter for networked systems with random parameter matrices and correlated noises under deception attacks |
| Parallel session J: CFE | Sunday 17.12.2023 | 16:00 - 18:05 |
| Session CO247 | Room: 236 |
| Topics in (structural) VAR modeling | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Ralf Brueggemann | Organizer: Ralf Brueggemann |
| B1617: D. Dzikowski, C. Jentsch | |
| Structural periodic vector autoregressions under general linear restrictions | |
| A0400: A. Camehl, T. Wozniak | |
| What do data say about time-variation in monetary policy shock identification? | |
| A0919: T. Haertl | |
| Identifying proxy VARs with restrictions on the forecast error variance | |
| A1542: L. Fanelli, G. Angelini, L. Neri | |
| Invalid proxies and volatility changes | |
| A1044: C. Jentsch, K. Lunsford | |
| Asymptotically valid bootstrap inference for proxy SVARs |
| Session CO036 | Room: 258 |
| Topics in econometrics with financial applications | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Yuqian Zhao | Organizer: Yuqian Zhao |
| A1203: S. Yu, Y. Li, I. Nolte, S. Nolte | |
| Nonparametric range-based estimation of integrated variance with episodic extreme return persistence | |
| A1389: B. Chen | |
| Panel VAR model with latent group structures | |
| A1416: Y. Zhao | |
| Detecting multiple changes in linear models with heteroscedastic errors | |
| A1477: J. Chen, G. Xu | |
| Group network multivariate GARCH | |
| A1580: X. Li, J. Yuan | |
| Deep learning for VAR modelling and forecasting |
| Session CO017 | Room: 260 |
| Macroeconomic uncertainty and textual analysis | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Svetlana Makarova | Organizer: Wojciech Charemza, Svetlana Makarova |
| A0519: S. Lee, D. Tuckett, R. Nyman | |
| Tracking economic policy uncertainty through the relative sentiment shift | |
| A0526: K. Rybinski | |
| Political leadership and economic policy uncertainty: Analysis of US presidents' speeches | |
| A0649: M.E. Bontempi, L. Bottazzi | |
| Heterogeneity of covenants violations, and corporate behavior | |
| A0792: J. Janecki | |
| Assessing consumers' inflation expectations in Euro area countries using entropy measures | |
| A1012: S. Makarova, S. Bartha, M.E. Bontempi | |
| Economic uncertainty measures, experts and ChatGPT |
| Session CO407 | Room: 261 |
| Forecasting: Theory and practice | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Massimiliano Caporin | Organizer: Tommaso Di Fonzo, Massimiliano Caporin |
| A1886: L. Fenga | |
| Forecasting with exponential smoothing models using bootstrapped model selection and parameter estimation | |
| A0851: D. Girolimetto, M. Caporin, T. Di Fonzo | |
| Exploiting intraday decompositions in realized volatility forecasting: A forecast reconciliation approach | |
| A1638: R. Hollyman | |
| Hierarchies everywhere: Managing \& measuring uncertainty in hierarchical time series | |
| A1297: T. Di Fonzo, D. Girolimetto, R. Hyndman, G. Athanasopoulos | |
| Cross-temporal probabilistic forecast reconciliation: Methodological and practical issues | |
| A0442: M. Caporin, G. Bonaccolto, J. Shahzad | |
| Spillover and quantile-spillover indexes: Simulation-based evidences |
| Session CO168 | Room: 262 |
| Large-dimensional panel time series (virtual) | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Maria Grith | Organizer: Degui Li |
| A1221: M. Grith, Y. Chen, H.L.H. Lai | |
| Neural tangent kernel in implied volatility forecasting: A nonlinear functional autoregression approach | |
| A1231: C. Huang, V. Chernozhukov, I. Fernandez-Val, W. Wang | |
| Arellano-bond LASSO estimator for long panel dynamic linear models | |
| A1261: Y. Yan, J. Gao, B. Peng | |
| Time-varying vector error-correction models: Estimation and inference | |
| A1284: Y. Wang, T. Otsu | |
| Panel data with high-dimensional factors with application to peer-effects analysis in networks | |
| A1525: W. He, M. Xiaoling, W. Zhong, H. Zhu | |
| Multiperiod dynamic portfolio choice: When high dimensionality meets return predictability |
| Session CO025 | Room: 354 |
| Advancements of survival and duration models | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Ralf Wilke | Organizer: Ralf Wilke |
| A0321: M. Wojtys, Y. Wei, L. Sorrell, P. Rowe | |
| Bivariate copula regression models for semi-competing risks with application to kidney transplant data | |
| A0521: T. Emura, H. Michimae | |
| Bayesian ridge regression for survival data based on a vine copula based prior | |
| A0551: R. Braekers | |
| Describing the dependence structure of clustered right-censored event times through factor copula functions. | |
| A1017: M. Hiabu, S. Bischofberger, E. Mammen, J.P. Nielsen | |
| Smooth backfitting for additive hazard rates | |
| A1485: M.S.S. Lo, R. Wilke, M. Hiabu | |
| Identifiability and estimation of the competing risks model under exclusion restrictions |
| Session CO126 | Room: Virtual R02 |
| Advances in quantitative finance and insurance | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Asmerilda Hitaj | Organizer: Elisa Mastrogiacomo, Asmerilda Hitaj |
| A0729: A. Hitaj, E. Mastrogiacomo, E. Molho | |
| Robust multiobjective mean-conditional value at risk optimization: Applications to energy portfolios | |
| A0828: M. Kaucic | |
| A many-objective evolutionary algorithm for a portfolio optimization problem with ESG and diversification goals | |
| A1077: E. Mastrogiacomo, M. Rocca | |
| Multi-objective stochastic problems and their connections with multivariate risk measures | |
| A1122: M. Tarsia, E. Mastrogiacomo | |
| Equilibrium strategies in time-inconsistent stochastic control problems with constraints: Necessary conditions | |
| A1033: F. Vanni | |
| Portfolio allocation: The advantage of using network approach |
| Session CC503 | Room: 257 |
| Forecasting | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Robinson Kruse-Becher | Organizer: CFE |
| A0206: B. Kozyrev, O. Holtemoeller | |
| Forecasting economic activity with a neural network in uncertain times: Application to German GDP | |
| A1363: M. Dauber, J. Lawrenz | |
| The decay of cay | |
| A1463: J. Janczura | |
| Expectile regression averaging method in probabilistic forecasting of electricity prices | |
| A1651: P. Letixerant, R. Kruse-Becher | |
| Macroeconomic survey forecasting in times of crises | |
| A1736: J. Andre, M. Bessec | |
| A mixed-frequency factor model for nowcasting French GDP |
| Session CC510 | Room: 259 |
| Macroeconometrics | Sunday 17.12.2023 16:00 - 18:05 |
| Chair: Johan Lyhagen | Organizer: CFE |
| A1272: I. Panovska, L. Donayre | |
| The speed of state-level recoveries | |
| A1456: P. Goemans | |
| A new macroeconomic uncertainty index for the euro area countries | |
| A1788: D. Di Francesco, A. Moneta, M. Martinoli, R. Seri | |
| Data-driven identification and estimation of DSGE models by non-Gaussianity | |
| A1852: A. Celani, G. Ascari, P. Bonomolo | |
| The macroeconomic effects of inflation expectations: The distribution matters | |
| A1535: K. Heinisch | |
| Step by step: A quarterly evaluation of EU commissions' GDP forecasts |
| Parallel session M: CMStatistics | Monday 18.12.2023 | 08:30 - 10:10 |
| Session EI008 (Special Invited Session) | Room: 350 |
| Advanced statistical methods for energy and finance | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Boris Buchmann | Organizer: Yanrong Yang |
| B1772: G. Mueller, D. Nickelsen, S. Uhl | |
| Advanced methods for modelling and forecasting electricity prices | |
| B1965: K. Lu, T. Leung | |
| Pairs Trading for Levy-driven Ornstein-Uhlenbeck processes | |
| B0171: B. Buchmann | |
| Weak subordination of multivariate Levy processes | |
| B1983: A. Ferreira | |
| Extremes at small times and applications to measuring jump process activity |
| Session EO078 | Room: 340 |
| Statistical analysis of complex structured data: Clustering and smoothing | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Semhar Michael | Organizer: Weixin Yao |
| B0207: S. Sarkar, A. Asilkalkan, X. Zhu | |
| Finite mixture of hidden Markov models for tensor-variate time series data | |
| B0427: S. Michael, A. Simpson, C. Saunders, D. Borchert, L. Tang | |
| Mixture modeling of data with hierarchy | |
| B1202: J. Yu | |
| Uniform design motivated basis selection methods for smoothing spline regression | |
| B1211: R. Di Mari | |
| A two-step estimator for multilevel latent class analysis |
| Session EO080 | Room: 348 |
| New approaches on the inference and modeling of network data | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Wen Zhou | Organizer: Wen Zhou |
| B0734: Y. Zhao, X. Li, Q. Pan, N. Hao | |
| Heterogeneous block covariance model for community detection | |
| B0766: S. Wu, G. Xu, J. Zhu | |
| A general latent embedding approach for modeling high-dimensional hyperlinks | |
| B0794: Y. Zhang, M. Shao | |
| Distribution-Free matrix prediction under arbitrary missing pattern | |
| B0882: T. Li | |
| Approximate inference of network diffusion sources by graphical models |
| Session EO134 | Room: 351 |
| Flexibility of Bayesian mixture models in spatial applications | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Mario Beraha | Organizer: Alessandra Guglielmi |
| B0333: L. Aiello, S. Banerjee | |
| Modeling spatial health disparities using disease maps | |
| B0368: A. Cremaschi, M. De Iorio, T. Wertz | |
| Repulsion, chaos and equilibrium in mixture models | |
| B0382: J. Pavani, F. Quintana | |
| Spatiotemporal modelling for multiple mosquito-borne diseases: A flexible Bayesian clustering approach | |
| B1340: A. Mozdzen, G. Kastner, T. Krisztin | |
| Studying the impact of agricultural subsidies across Europe using a Bayesian spatiotemporal clustering model |
| Session EO298 | Room: 352 |
| Recent advances in Bayesian structure learning | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Arkaprava Roy | Organizer: Arkaprava Roy |
| B0714: P. Samartsidis, S. Seaman, D. De Angelis | |
| A modularized Bayesian factor analysis model for policy evaluation | |
| B1165: N. Anceschi, F. Ferrari, H. Mallick, D. Dunson | |
| Joint additive factor analysis for multi-omics data integration | |
| B1200: N. Guha, J. Datta | |
| A random projection based technique for change point estimation in high dimension | |
| B1271: J. Datta, N. Polson | |
| Quantile importance sampling |
| Session EO214 | Room: 353 |
| Risk modeling and analysis of extreme events | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Marta Nai Ruscone | Organizer: Roberta Pappada, F Marta L Di Lascio |
| B0675: V. Carcaiso, I. Antoniano-Villalobos, I. Prosdocimi | |
| Where do extremes come from? Dependent mixtures for block maxima | |
| B0421: A.C. Cebrian, E. Schliep, A. Gelfand, J. Asin, J. Castillo-Mateo | |
| Spatiotemporal modeling of extreme events and analysis of their extent | |
| B0842: A. Guolo | |
| Accounting for measurement errors in control risk regression through structural and functional approaches | |
| B0823: M. Restaino, M. Niglio, M. La Rocca | |
| Bootstrapping asymmetric binary regression models for massive unbalanced datasets |
| Session EO055 | Room: 354 |
| (Non-)parametric survival analysis: From simulations to testing | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Dennis Dobler | Organizer: Dennis Dobler, Marc Ditzhaus |
| B0874: T. Fernandez, N. Rivera | |
| A general framework for the analysis of kernel-based tests: Applications to survival analysis | |
| B1374: M. Thurow, I. Dormuth, C. Sauer, M. Ditzhaus, M. Pauly | |
| How to simulate realistic survival data? A simulation study to compare realistic simulation models | |
| B0389: M. Munko, M. Ditzhaus | |
| Surviving the multiple testing problem: RMST-based tests in general factorial designs | |
| B0488: K. Moellenhoff, A. Tresch | |
| Survival analysis under non-proportional hazards: Investigating non-inferiority or equivalence in time-to-event data |
| Session EO042 | Room: 355 |
| Duration data | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Yoann Potiron | Organizer: Yoann Potiron |
| B1228: O. Scaillet, Y. Potiron, S. Yu | |
| Estimation of integrated intensity in Hawkes processes with time-varying baseline | |
| B1299: Y. Potiron, O. Scaillet, S. Yu | |
| High-frequency estimation of Ito semi martingale baseline for Hawkes processes | |
| A1420: G. Toscano, S. Scotti, I. Raffaelli | |
| High-frequency goodness-of-fit testing of Hawkes-driven stochastic volatility models | |
| B1558: T. Ogihara | |
| Maximum-likelihood estimation for jump-diffusion processes with nonsynchronous observations |
| Session EO272 | Room: 356 |
| Experimental designs: Constructions and application | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Stella Stylianou | Organizer: Stella Stylianou, Stelios Georgiou |
| B1386: D. Athanasaki | |
| Exploring composite design: Investigating alternatives in response surface methodology | |
| B1438: A.S.S. Alamri | |
| Eliciting preferences for adoption of autonomous vehicles in Saudi Arabia: Discrete choice experiments | |
| B1467: O. Alhelali, S. Stylianou, S. Georgiou | |
| Designs for computer experiments from sequences with zero autocorrelation function | |
| B1698: T. Dharmaratne, A. De Livera, S. Georgiou, S. Stylianou | |
| Application of supersaturated design-based statistical methods on observational data for variable selection |
| Session EO287 | Room: 357 |
| Cyber risk modeling and assessment | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Abdelaati Daouia | Organizer: Abdelaati Daouia |
| B1700: C. Gourieroux | |
| The risk of random sets with applications to basket derivatives | |
| B1484: C. Hillairet | |
| Hawkes processes, Malliavin calculus, and application to cyber-insurance derivatives | |
| B0777: O. Lopez | |
| Prior distribution for cyber insurance modeling and applications to risk transfer | |
| B1515: A. Usseglio-Carleve, G. Stupfler, A. Daouia | |
| Accurate Gaussian inference about extreme expectiles and application in cyber risk |
| Session EO273 | Room: 401 |
| Non-regularity in statistical inference for stochastic processes | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Kengo Kamatani | Organizer: Kengo Kamatani |
| B0662: S. Eguchi | |
| Robustified Gaussian quasi-likelihood inference in YUIMA | |
| B0789: Y. Shimizu | |
| Statistical inference for Gaussian processes with small noise asymptotics | |
| B0891: B. Brahmantio | |
| Bayesian inference of mixed Gaussian phylogenetic models | |
| B0933: T. Takabatake | |
| Likelihood analysis of continuous-time Gaussian moving average processes having scaling properties |
| Session EO339 | Room: 403 |
| Simultaneous and selective statistical inference | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Thorsten Dickhaus | Organizer: Thorsten Dickhaus |
| B0511: J. Goeman | |
| Cluster extent inference revisited: Quantification and localization of brain activity | |
| B0613: R. Heller, A. Solari | |
| Simultaneous directional inference | |
| B0988: P. Grunwald | |
| Beyond Neyman-Pearson: Setting alpha after the fact | |
| B0628: T. Dickhaus | |
| Bayes factors and e-values for the simultaneous analysis of many contingency tables |
| Session EO054 | Room: 404 |
| Spatial data science | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Philipp Otto | Organizer: Philipp Otto |
| B0377: A.G. Bille | |
| Accounting for spillovers effects and temporal dynamics on the impact of renewables on labor force: A world perspective | |
| B0833: P. Colombo, P. Maranzano, A. Fasso | |
| Block bootstrap adjustment for heteroskedastic Gaussian process | |
| B1065: R. Mattera, R. Cerqueti, P. Durso, V. Vitale | |
| Estimation of spatially clustered panel data models | |
| B1055: C. Mare, P. Otto | |
| Space-time effects in cryptocurrencies: The spatiotemporal ARCH model |
| Session EO175 | Room: 414 |
| Statistical power to Bayesian assurance in clinical trials | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Din Chen | Organizer: Din Chen |
| B1245: D. Chen | |
| Statistical power to Bayesian assurance in superiority clinical trials | |
| B1311: M. Kirchner, M. Kieser, S. Erdmann, H. Goette | |
| Utility-based optimization of phase II/III programs considering success probabilities for phase III | |
| B1521: A. Ring, D. Chen, R. El-Galta | |
| Complex assurance considerations when designing biosimilar trials | |
| B1537: M.R. Lange | |
| Strategies for improving the assessment of the probability of success in late-stage drug development |
| Session EO174 | Room: 424 |
| EcoSta journal session | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Masayuki Hirukawa | Organizer: Erricos Kontoghiorghes |
| B1439: M. Hirukawa | |
| Sufficient dimension reduction meets two-sample regression estimation | |
| A0372: M. Nagl, M. Nagl, D. Roesch | |
| Non-linearity and the distribution of market-based loss rates | |
| B1254: J. Runge | |
| Recent advances in causal discovery for time series and optimal adjustment for causal effect estimation | |
| B1471: H. Dehling, S.K. Schmidt, M. Wornowizki, R. Fried, D. Giraudo | |
| Test for constancy of the variance in a time series |
| Session EO374 | Room: 442 |
| Independence properties and invariant measures | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Efoevi Angelo Koudou | Organizer: Efoevi Angelo Koudou |
| B0751: M. Sasada | |
| Yang-Baxter maps and independence preserving property | |
| B1270: B. Kolodziejek | |
| A class of lattice models with new scaling exponents. | |
| B1553: J. Wesolowski | |
| Independence properties of the Kummer distribution and related characterizations |
| Session EO355 | Room: 445 |
| Causal inference in social sciences: Methods and applications | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Massimo Cannas | Organizer: Emiliano Sironi, Massimo Cannas |
| B0358: D. Failli, B. Arpino | |
| The impact of offline social networks on the age digital divide | |
| B0594: G. Grossi, A. Mattei, G. Papadogeorgou | |
| SMaC: Spatial matrix completion method | |
| B1053: M. Giacalone, M. Giacalone, E. Nissi | |
| Multicollinearity in treatment evaluation: A comparison between Lp-norm and least squares estimators | |
| B0914: M. Di Gregorio, Z.T. Simonella | |
| No causation without manipulation: The public responsibility of science and policy making |
| Session EO216 | Room: 446 |
| Biostatistical methods in Alzheimer's disease and aging research | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Maria Josefsson | Organizer: Maria Josefsson |
| B0355: T.D. Tran | |
| Latent Ornstein-Uhlenbeck models for Bayesian analysis of multivariate longitudinal categorical responses | |
| B0478: T. Gorbach, J. Carpenter, C. Frost, M. Josefsson, A. MacDougall, J. Nicholas, L. Nyberg | |
| Practical approach for missing data sensitivity analyses in joint modelling of cognition and dementia risk | |
| B0829: D. Nevo, M. Gorfine | |
| Causal inference for semi-competing risks data with application to Alzheimer's disease | |
| B1130: J. Williams | |
| Multistate Markov models: Application to dementia progression |
| Session EO251 | Room: 447 |
| Recent development on statistical analysis of complex dependent data | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Lujia Bai | Organizer: Weichi Wu |
| B1339: D. Kurisu, T. Otsu | |
| Nonparametric inference on intrinsic means | |
| B1350: S.S. Dhar, P. Guha Niyogi | |
| Comparison of the slops in functional regression under arbitrary transformations | |
| B1382: L. Bai, Q. Hu, W. Wu | |
| Testing and estimation of first-order structural changes in locally stationary functional time series | |
| B1368: S. Chandna | |
| Spectral estimation of latent structure in networks with covariates |
| Session EO041 | Room: 455 |
| Projection pursuit II | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Nicola Loperfido | Organizer: Nicola Loperfido |
| B0750: N. Loperfido | |
| Generalized tensor eigenpairs for moment-based projection pursuit | |
| B0692: C. Franceschini, N. Loperfido | |
| Projection pursuit: An empirical application to Italian primary school children | |
| B1493: H. Zhang, D. Cook, U. Laa, N. Langrene, P. Menendez | |
| Visual diagnostics for constrained optimization with application to guided tours | |
| B2004: J. Cabrera, Y. Duan | |
| Differential Projection pursuit methods and its applications to differential experiments |
| Session EO354 | Room: 458 |
| Topics in non-Euclidean statistics | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Andrew Wood | Organizer: Andrew Wood |
| B0523: L. Maestrini, J. Scealy, F. Hui, A. Wood | |
| Multiplicative semiparametric regression for manifold-valued responses | |
| B1059: S. Kato, T. Ito | |
| A mixed effects model for cylindrical data with application to small area estimation | |
| B1207: A. Wood | |
| Statistical models and methods for data on the hyperboloid | |
| B1479: V. Patrangenaru | |
| On data analysis on Stratified spaces, the origin of the COVID-19 pandemic and face analysis |
| Session EO164 | Room: Virtual R01 |
| Advanced statistical methods for genetics and genomic data | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Mengyun Wu | Organizer: Mengyun Wu |
| B0742: X. Luo | |
| Identification of cell-type-specific spatially variable genes accounting for excess zeros | |
| B0878: X. Qin, S. Ma, M. Wu | |
| Supervised heterogeneous network estimation via survival-based Bayesian graphical models | |
| B0883: Y. Xu, F. Xu, S. Ma, Q. Zhang | |
| Robust transfer learning in high-dimensional GLM via gamma-divergence | |
| B0974: X. Shi | |
| A general framework for identifying hierarchical interactions and its application to genomics data |
| Session EC466 | Room: 335 |
| Non- and semi- parametric statistics | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Keisuke Yano | Organizer: CFE-CMStatistics |
| B1501: G. Keilbar, L. Chen, W. Wang | |
| Many regression discontinuity estimators for panel data | |
| B1707: D. Strenger, S. Hoermann | |
| Measuring dependence between a scalar response and a functional covariate | |
| B1767: S. Bonnini, M. Borghesi | |
| Inference in a model for count data with application to Industry 4.0: The permutation approach | |
| B1804: M. Zetlaoui, P. Bertail | |
| Efficiency bound under identifiability constraints in semiparametric models |
| Session EC549 | Room: 444 |
| Biomedical data analysis | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Jonathan Stewart | Organizer: CFE-CMStatistics |
| B0390: H. Guo | |
| The impact of the major histocompatibility complex region on causal discoveries in Mendelian randomization studies | |
| B1900: L. Tardella, D. Passaro, G. Jona Lasinio, T. Fragasso, V. Raggi, Z. Ricci | |
| Prediction of kidney failure using electronic medical records | |
| B1744: M. Palma, R. Keogh, A. Wood, G. Muniz Terrera, J. Barrett | |
| Bayesian joint model for time-to-event and longitudinal markers with association based on within-individual variability | |
| B1513: F. Palacios Rodriguez, F.A. Chalub, A. Gomez Corral, M. Lopez Garcia | |
| Transmission of antibiotic-resistant bacteria explained with a Markov chain model |
| Session EC465 | Room: 457 |
| High-dimensional statistics | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Garth Tarr | Organizer: CFE-CMStatistics |
| B1565: R. Ando, F. Komaki | |
| On high-dimensional asymptotic properties of model averaging estimators | |
| B1880: F. Feser, M. Evangelou | |
| Sparse-group SLOPE: Adaptive bi-level selection with FDR-control | |
| B1901: R. Zoh | |
| An approximate Bayes factor-based high dimensional MANOVA using random projections | |
| B1894: M. Demosthenous, C. Gatu, E. Kontoghiorghes | |
| Computational strategies for regression model selection in the high-dimensional case |
| Parallel session M: CFE | Monday 18.12.2023 | 08:30 - 10:10 |
| Session CO019 | Room: 227 |
| Copulas, instruments, lasso, and cost-sensitive learning in high dimensions | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Artem Prokhorov | Organizer: Artem Prokhorov |
| A0574: S. Anatolyev, M. Smirnov | |
| Many instruments under data clustering | |
| A0583: A. Prokhorov, V. Zelenyuk, C. Parmeter | |
| On robust causal inference in models of firm productivity and efficiency in the presence of many environmental variables | |
| A0749: J.W.Y. Leung, R. James, A. Prokhorov | |
| Copula and optimal transport in finance | |
| A0870: R. James, A. Prokhorov | |
| Bi-objective cost-sensitive machine learning: Predicting stock return direction using option prices |
| Session CO240 | Room: 236 |
| Structural breaks in time series | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Anton Skrobotov | Organizer: Anton Skrobotov |
| A0306: E. Kurozumi, T. Tayanagi | |
| Change point estimators with the weighted objective function when estimating breaks one at a time | |
| A0813: A. Skrobotov, E. Kurozumi | |
| Improving the accuracy of bubble date estimators under time-varying volatility | |
| A0966: P. Rodrigues | |
| Testing for multiple structural breaks in multivariate long-memory regression models | |
| A1341: P. Jiang | |
| Testing for structural change in heterogeneous panels using common correlated effects estimators |
| Session CO259 | Room: 256 |
| Theory, design, and financial applications of neural networks | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Maria Grith | Organizer: Maria Grith |
| A1472: G. Finocchio, J. Schmidt-Hieber | |
| Posterior contraction for deep Gaussian process priors | |
| A0908: K. Klieber, P. Goulet Coulombe, M. Frenette | |
| From reactive to proactive volatility modeling with hemisphere neural networks | |
| A1302: C. Zhang | |
| Graph neural networks for forecasting multivariate realized volatility with spillover effects | |
| A1084: X. Bayer, N. Hautsch, R. Reisenhofer | |
| HARNet: A convolutional neural network for realized volatility forecasting |
| Session CO026 | Room: 257 |
| Climate change econometrics and financial markets | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Luca De Angelis | Organizer: Luca De Angelis |
| A1176: F. Parla, A. Cipollini | |
| Climate risk and investment in equities in Europe: A panel SVAR approach | |
| A1847: G. Angelini, L. De Angelis, L. Fanelli, M.M. Sorge | |
| Identification of climate policy uncertainty shocks: A proxy-SVAR approach | |
| A1890: F.S. Lucidi | |
| The effects of temperature shocks on energy prices and inflation in the Euro Area | |
| A1687: L. De Angelis, E. Campiglio, P. Neri, G. Scalisi | |
| Nonlinear impacts of transition risk in CDS markets |
| Session CO262 | Room: 259 |
| Advances in credit risk modelling | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Raffaella Calabrese | Organizer: Raffaella Calabrese |
| A1244: C. Feng, E. Altman, Z. Li, X. Liang | |
| The impact of economic shocks on the credit ratings of Chinese listed firms | |
| A1067: Z. Wu, Y. Dong, Y. Li, B. Shi | |
| A prompt-based deep learning method for leveraging textual information in enhancing default prediction | |
| A0822: Y. Chen, R. Calabrese, B. Martin-Barragan | |
| A novel interpretation method for explaining machine learning survival models | |
| A1729: F. Sigrist, N. Leuenberger | |
| Machine learning for credit risk: Multi-period prediction, frailty correlation, loan portfolios, and tail probabilities |
| Session CO204 | Room: 261 |
| Forecast evaluation | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Timo Dimitriadis | Organizer: Timo Dimitriadis |
| A0514: J. Fosten, V. Corradi, D. Gutknecht | |
| Predictive ability tests with possibly overlapping models | |
| A0903: T. Dimitriadis | |
| Continuous monitoring of systemic risks | |
| A1041: J. Taylor | |
| Probabilistic forecast aggregation with statistical depth | |
| A1152: X. Meng, J. Taylor, J. Curtis | |
| Generalized linear pools for combining probabilistic forecasts |
| Session CC499 | Room: 258 |
| Financial econometrics | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Alexander Meyer-Gohde | Organizer: CFE |
| A1741: P. He, P. Shevchenko, N. Kordzakhia, G. Peters | |
| Multi-Factor Polynomial DIffusion Models and Inter-Temporal Futures Dynamics in Energy Markets | |
| A1871: M. Ficura, J. Witzany | |
| Historical calibration of SVJD models with deep learning | |
| A1885: J. Witzany, M. Ficura | |
| A comparison of neural networks and Bayesian approaches for the Heston model estimation | |
| A0505: B. van der Sluis | |
| Grouped heterogeneity in Markov-switching panel models |
| Session CC539 | Room: 260 |
| Econometrics hypothesis testing | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Andrej Srakar | Organizer: CFE |
| A1625: J. Beyhum, J. Striaukas | |
| Tuning-free testing of factor regression against factor-augmented sparse alternatives | |
| A0231: J. Olmo, J. Hualde | |
| Residual-based cointegration tests between combinations of I(0) and I(1) processes | |
| A1298: M.M. Sorge, L. Fanelli, G. Angelini | |
| Is time an illusion? A bootstrap likelihood ratio test for shock transmission delays in DSGE models | |
| A1734: S. Muhinyuza, S. Drin, S. Mazur | |
| A test on the location of tangency portfolio for small sample size and singular covariance matrix |
| Session CC506 | Room: 262 |
| Machine learning for CFE | Monday 18.12.2023 08:30 - 10:10 |
| Chair: Massimiliano Caporin | Organizer: CFE |
| A1497: E.-J. Senn, M.T. Phan | |
| LongFinBERT: A Language Model for Very Long Financial Documents | |
| A1645: M. Joets, C. Brunetti, V. Mignon | |
| Reasons behind words: OPEC and the oil market | |
| A1418: J. Chen, C. Agiropoulos | |
| Covid-19 and commodity markets: A hybrid approach to temporal and spatial clustering |
| Parallel session N: CMStatistics | Monday 18.12.2023 | 10:40 - 12:20 |
| Session EV486 | Room: Virtual R02 |
| Applied statistics | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Vince Lyzinski | Organizer: CFE-CMStatistics |
| B1995: D. Nguyen | |
| A Bayesian trivariate joint model of kidney disease progression, recurrent cardiovascular events, and terminal event | |
| B1996: K. Young, L. Bantis | |
| Statistical inference for the comparison of two correlated biomarkers using the partial volume under the ROC surface | |
| B1999: S. Jokubaitis, D. Celov | |
| A soft-clustering approach for regional-sectoral EU business cycle synchronization | |
| B1146: A. Christidis, G. Cohen Freue | |
| Robust multi-model subset selection |
| B0200: F. Lindgren | |
| Non-stationary distributional regression methods for historical climate analysis | |
| B0201: D. Hammerling, W. Daniels, M. Jia | |
| Methane emission detection, localization and quantification on oil and gas facilities | |
| B0202: M. Katzfuss | |
| Non-Gaussian emulation of climate models via scalable Bayesian transport maps |
| Session EO381 | Room: 335 |
| Recent advances in copula models | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Thomas Nagler | Organizer: Thomas Nagler |
| B0362: A. Hanebeck, C. Czado | |
| Multivariate analysis of mortality data using time-varying copula state space models | |
| B1192: E. Griesbauer, C. Czado, A. Frigessi, I. Hobaek Haff | |
| Vine copula based synthetic data generation for classification: A privacy and utility analysis | |
| B1194: J. Gauss, T. Nagler | |
| Parameter estimation in high-dimensional vine copula models | |
| B1545: E. Perrone, R. Fontana, F. Rapallo | |
| Contingency tables with structural zeros and discrete copulas |
| Session EO191 | Room: 340 |
| Statistical modelling with complex data | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Garth Tarr | Organizer: Garth Tarr |
| B0281: S. Lotspeich, B. Richardson, P. Baldoni, K. Enders, M. Hudgens | |
| Challenges in quantifying the HIV reservoir from dilution assays: Overcoming missingness and misclassification | |
| B0506: X. Xu, S. Greven, M. Samuel | |
| Unravelling complex diet-gut microbiome-host health interaction by mixture of experts models | |
| B0530: E. Guilbault, I. Renner, E. Beh, M. Mahony | |
| How to accommodate uncertain observations and data quality in species distribution modeling using point process models | |
| B0606: K. Ramsay, D. Spicker | |
| Differentially private projection depth-based medians |
| Session EO305 | Room: 348 |
| New directions in network data methodology | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Srijan Sengupta | Organizer: Srijan Sengupta |
| B0643: F. Pavone | |
| Phylogenetic latent position models | |
| B1079: S. Roy, S. Park, M. Nunes | |
| New directions in constrained spectral clustering for networks | |
| B1304: G. Mukherjee | |
| A back-fitting based MCEM algorithm for scalable estimation in multinomial probit model with multilayer network linkages | |
| B1594: S. Banerjee, S. Bhamidi, X. Huang | |
| Exploration-driven networks |
| Session EO331 | Room: 351 |
| Advances in Bayesian modeling and computation | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Luca Maestrini | Organizer: Luca Maestrini |
| B0438: D. Gunawan, D. Gunawan, A. Zammit Mangion, B. Vu | |
| R-VGAL: A sequential variational Bayes algorithm for generalized linear mixed models | |
| B0482: C. Grazian | |
| Approximate Bayesian computation for long memory processes | |
| B0559: K.-D. Dang, L. Maestrini | |
| Variational inference for structural equation models | |
| B1066: T. Stindl | |
| Bayesian estimation for some self-exciting point processes |
| Session EO416 | Room: 352 |
| Advances in change-point analysis | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Yining Chen | Organizer: Yining Chen |
| B1223: J. Li, P. Fearnhead, P. Fryzlewicz, T. Wang | |
| Automatic change-point detection in time series via deep learning | |
| B1396: H. Maeng, T. Wang, P. Fryzlewicz | |
| Adaptive high-dimensional change-point detection from the bottom up | |
| B1873: C. Truong | |
| Efficient convolutional sparse coding with a $L_0$ constraint | |
| B1882: Y. Chen, T. Wang, R. Samworth | |
| Inference in high-dimensional online changepoint detection |
| Session EO170 | Room: 353 |
| Recent advances in Stein's method and statistical applications | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Bruno Ebner | Organizer: Bruno Ebner |
| B0836: R. Gaunt | |
| Bounds for distributional approximation in the multivariate delta method by Steins method | |
| B0917: A. Fischer, R. Gaunt, B. Ebner, Y. Swan, B. Picker | |
| Stein's method for estimation purposes | |
| B1318: J. Allison, J. Ngatchou-Wandji, J. Visagie, T. Nombebe, L. Santana | |
| On classes of consistent tests for the Pareto distribution with application to frailty models | |
| B1064: Y. Swan | |
| Wasserstein bounds through Stein's method with bespoke derivatives |
| Session EO056 | Room: 354 |
| Non- and semiparametric survival analysis with covariates | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Merle Munko | Organizer: Dennis Dobler, Marc Ditzhaus |
| B1010: R. Graf, S. Friedrich, D. Dobler | |
| Random forests for prediction of treatment effect and treatment group in survival data | |
| B0909: E. Musta, T. Jacobs, M. Fiocco | |
| A competing risks analysis with cause-specific cure | |
| B0800: P. Blanche, T. Scheike | |
| On logistic regression to estimate treatment effects with observational, right censored, competing risks data. | |
| B1248: D. Edelmann | |
| Testing for association with survival in genome-wide analysis studies: Overcoming limitations and innovating approaches |
| Session EO349 | Room: 356 |
| Safe, anytime-valid inference | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Peter Grunwald | Organizer: Claudia Di Caterina |
| B0554: M. Lindon | |
| Anytime-valid linear models and regression adjusted causal inference in randomized experiments | |
| B0585: S. Arnold, J. Ziegel | |
| Sequential model confidence sets | |
| B0557: M. Perez, T. Lardy | |
| Anytime-valid permutation tests and general tests of symmetry | |
| B0286: H. Wang, A. Ramdas | |
| Sequential tests with extended nonnegative supermartingales: A frequentist approach to improper priors |
| Session EO236 | Room: 357 |
| Extremes and dependence | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Marie Kratz | Organizer: Marie Kratz |
| B0424: S. Singha, M. Kratz, S. Vadlamani | |
| From geometric quantiles to halfspace depths: A geometric approach for extremal behavior | |
| B0502: D. Lauria, S. Rachev, A. Trindade | |
| Global and tail dependence: A differential geometry approach | |
| B0504: V. Fasen-Hartmann, B. Das | |
| Financial risk measures in complex networks: The effect of asymptotic independence | |
| B1602: A. Khorrami Chokami, M. Kratz, M. Dacorogna | |
| Exploring tail dependence between time series via concomitants |
| Session EO332 | Room: 403 |
| Recent advances in quantile regression models | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Luca Merlo | Organizer: Luca Merlo |
| B0324: R. Gerlach, G. Storti, A. Naimoli | |
| Using quantile time series and historical simulation to forecast financial risk multiple steps ahead | |
| B0582: B. Melly, M. Pons | |
| Minimum distance estimation of quantile panel data models | |
| B0524: M. Geraci, A. Farcomeni | |
| Quantile ratio regression | |
| B0841: B. Foroni, L. Merlo, L. Petrella | |
| Quantile and expectile copula-based hidden Markov regression models for the analysis of the cryptocurrency market |
| Session EO142 | Room: 414 |
| y-SIS - Advances in Robust Statistical Methods for Complex Data | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Giorgia Zaccaria | Organizer: Giorgia Zaccaria |
| B0560: S.D. Tomarchio, A. Punzo, A. Bekker, J. Ferreira | |
| A new look at the Dirichlet distribution with applications in model-based clustering | |
| B0667: A. Cappozzo, F. Ieva, A. Rossi | |
| Enhancing outlier detection in functional data via robustly adjusted functional boxplot | |
| B1209: M. Farne, A. Vouldis | |
| ROBOUT: A step-wise methodology for conditional outlier detection | |
| B1357: M. Welz | |
| Robust parameter estimation in discrete data |
| Session EO433 | Room: 424 |
| A challenge of developing statistical approaches for complex data | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Keisuke Yano | Organizer: Keisuke Yano |
| B0328: X. Li, F. Komaki | |
| Improved prediction for independent Poisson processes under Kullback-Leibler loss | |
| B0387: A. Okuno, R. Cao, K. Nakagawa, H. Shimodaira | |
| Optimal nonparametric classification via radial distance | |
| B0586: L. Kook, L. Kook | |
| Distributional regression with neural networks in R | |
| B1353: Y. Ohkubo | |
| Recent advances in the phylogenetic comparative methods |
| Session EO409 | Room: 442 |
| Regression models for latent structures | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Tobias Hepp | Organizer: Tobias Hepp |
| B0626: C. Griesbach, T. Hepp | |
| Confidence intervals for finite mixture regression based on resampling techniques | |
| B0827: C. Feldmann, S. Mews, R. Langrock | |
| Nonparametric modelling of periodic variation in hidden Markov models | |
| B0990: Q.E. Seifert, A. Thielmann, E. Bergherr, B. Saefken, T. Hepp | |
| Penalized regression splines in mixture density networks | |
| B1095: C. Staerk, J. Speller, F. Gude, A. Mayr | |
| Boosting robust distributional regression |
| Session EO432 | Room: 444 |
| Statistical learning for complex and high-dimensional data | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Qianqian Zhu | Organizer: Qianqian Zhu |
| B1259: L. Dai | |
| Metric learning via cross-validation | |
| B1103: Y. Zhang | |
| An efficient tensor regression for high-dimensional data | |
| B1526: Y. Qiu, B. Dai | |
| ReHLine: Regularized composite ReLU-ReHU loss minimization with linear computation and linear convergence | |
| B1929: Q. Zhu, W. Li, Y. Lin, G. Li | |
| An efficient multivariate volatility model for many assets |
| Session EO063 | Room: 446 |
| Flexible Bayesian approaches for complex problems in causal inference | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Michael Daniels | Organizer: Michael Daniels |
| B0456: M. Josefsson | |
| A Bayesian semi-parametric approach for incremental intervention effects in mortal cohorts | |
| B0498: S. Bhandari, M.J. Daniels, M. Josefsson, J. Siddique | |
| A Bayesian semi-parametric approach to causal mediation for longitudinal mediators and time-to-event outcomes | |
| B0755: C. Kim | |
| Confounder selection with Bayesian decision tree ensembles | |
| B1172: A. Caron, I. Manolopoulou, G. Baio | |
| Interpretability, regularization and uncertainty quantification in Bayesian causal inference |
| Session EO096 | Room: 455 |
| Topics on dimension reduction and covariance estimation | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Kuang-Yao Lee | Organizer: Kuang-Yao Lee |
| B0575: K. Kim | |
| On sufficient graphical models | |
| B1201: Z. Yu | |
| Deep nonlinear sufficient dimension reduction | |
| B1611: H.-H. Huang | |
| Sparse matrix estimation based on greedy algorithms and information criteria | |
| B1796: E.M. Issouani, P. Bertail, E. Gautherat | |
| Optimal penalty selection for high-dimensional covariance matrices with an application in NLP |
| Session EC484 | Room: 355 |
| Computational statistics and statistical modelling | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Jonathan Stewart | Organizer: CFE-CMStatistics |
| B1631: S. Heyder | |
| Exploiting independence in Gaussian importance sampling for Bayesian inverse problems | |
| B1763: J. Resin, T. Dimitriadis, J. Bracher, D. Wolffram | |
| Quantile-based approximation and decomposition of the Cramer distance | |
| B1855: E. Marceau | |
| Risk models defined on a family of tree-based Markov random fields with Poisson marginals | |
| B1918: I. Sousa | |
| Multiple longitudinal joint model with informative time measurements |
| Session EC543 | Room: 401 |
| Stochastic processes and applications | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Michal Balcerek | Organizer: CFE-CMStatistics |
| B1006: V. Kumar, N.S. Upadhye | |
| Modeling and simulation of first-come, first-served queueing system with impatient multiclass customers | |
| B1402: D. Miao | |
| Markov chain modeling of a limit order book with limit order arrivals following Markov modulated Poisson processes | |
| B1877: M. Balcerek, D. Krapf, R. Metzler, A. Wylomanska, K. Burnecki | |
| Modelling intermittent anomalous diffusion with switching fractional Brownian motion | |
| B1658: J. Soehl, L. Koorevaar, S. Tendijck | |
| Spectral calibration of time-inhomogeneous exponential Levy models |
| Session EC542 | Room: 404 |
| Spatial statistics | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Klaus Nordhausen | Organizer: CFE-CMStatistics |
| B1403: C. Peng | |
| Block-diagonal matrix-logarithmic covariance model for large spatial binary data | |
| B1441: T. Gyger, F. Sigrist, R. Furrer | |
| Iterative methods for full-scale Gaussian process approximations for large spatial data | |
| B1450: P. Kuendig, F. Sigrist | |
| Iterative methods for Vecchia-Laplace approximations for latent Gaussian process models | |
| B1845: M. Sipila, S. Taskinen, K. Nordhausen | |
| Nonlinear blind source separation exploiting spatial nonstationarity |
| Session EC550 | Room: 445 |
| Applied machine learning | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Stathis Gennatas | Organizer: CFE-CMStatistics |
| B0449: H. Masoumi Karakani | |
| Bayesian machine learning for bird call identification in soundscape analysis: An innovative approach | |
| B1137: P. Wojcik | |
| On track to a green future: New insights on the impact of train transport on Warsaw suburban real estate market | |
| B1633: N. Jullapech, F. Baksh, Z. Wang | |
| An ensemble approach to feature identification and prediction of antimicrobial peptide activity | |
| B1629: E. Bae, R. Shinohara | |
| Supervised machine learning for segmentation misclassification in neuroimaging |
| Session EC554 | Room: 447 |
| Applied statistics with complex data | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Johan Lyhagen | Organizer: CFE-CMStatistics |
| B1453: W. Zheng, M. Scott, C. Miller, A. Elliott | |
| Spatiotemporal data fusion method for soil moisture data | |
| B1556: S. Das, G.C. Granados Garcia, H. Ombao | |
| Measuring non-stationarity in large time series: A spectral unsupervised learning approach | |
| B1588: Y. Zhu, A. Simpkin | |
| Functional data analysis for diagnosis of coronary artery disease | |
| B1597: G. d Angella, C. Hennig | |
| Statistical delimitation of biological species based on genetic and spatial data |
| Session EC490 | Room: 457 |
| Methodological statistics | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Maria Brigida Ferraro | Organizer: CFE-CMStatistics |
| B1437: N. Weeraratne, L. Hunt, J. Kurz | |
| On U-estimation of principal components when $n < p$ | |
| B1664: J. Wang, E. Lock | |
| Multiple augmented reduced rank regression for pan-cancer analysis | |
| B1765: E. Biswas, D. Nordman, U. Genschel | |
| Bootstrap-based test of rotational symmetry in orientation data | |
| B1790: C. Amado, C. Rodrigues | |
| Aspects of statistical inference on interval-valued data |
| Session EC553 | Room: 458 |
| Statistical methods for applications | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Marialuisa Restaino | Organizer: CFE-CMStatistics |
| B1394: J. Aubray, F. Nicol, S. Puechmorel | |
| Regression on lie groups: Application to estimation of positions of a mobile | |
| B1567: J. Gross, A. Moeller | |
| Statistical properties of Cohen's d from linear regression | |
| B1478: K. Hayakawa, B. Yin | |
| The mean group estimators for multi-level autoregressive models with intensive longitudinal data | |
| B1764: A. Pathak, S. Dutta | |
| Predictions in multi-environment agricultural trials |
| Session EP001 | Room: Poster Virtual Room 2 |
| Poster Session II | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Cristian Gatu | Organizer: CFE, CFE-CMStatistics |
| A1585: M. Nakakita, T. Nakatsuma | |
| Efficiency improvement of Bayesian estimation by applying ASIS and its applicability | |
| A1628: R. Pascoal, A. Monteiro | |
| Risk neutral density estimation through Hermite polynomials | |
| B1618: T. Toyabe, T. Hoshino | |
| Positive-unlabeled survival data analysis | |
| B1813: K. Takahashi | |
| Statistical inferences for measures of multi-label classification | |
| A1984: C. Eleftheriou, D. Koursaros | |
| Unveiling influence in unregulated markets | |
| B1986: T. Nombebe, J. Allison, J. Visagie, L. Santana | |
| Investigating different parameter estimation techniques for the Lomax distribution | |
| B1987: N. D Angelo, G. Adelfio | |
| Minimum contrast for estimating point processes intensity |
| Parallel session N: CFE | Monday 18.12.2023 | 10:40 - 12:20 |
| Session CV497 | Room: Virtual R01 |
| Time series and forecasting | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Anindya Roy | Organizer: CFE |
| A1714: T. Takahashi, T. Mizuno | |
| Generation of synthetic financial time series by diffusion models | |
| A1811: J. Lee, Y. Eo | |
| Asymptotic properties of Bayesian inference for structural changes in multivariate regressions | |
| A1665: A. Pajor, J. Wroblewska, L. Kwiatkowski | |
| Bayesian evaluation of recursive multi-step-ahead path forecasts | |
| A1988: Y. Luo, M. Izzeldin | |
| Forecasting realized volatility: A hybrid model integrating BiLSTM with HAR-type models |
| Session CO107 | Room: 227 |
| Econometrics and statistics for sustainable economics | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Paolo Maranzano | Organizer: Simone Boccaletti, Paolo Maranzano |
| A0485: P. Otto, O. Dogan, S. Taspinar | |
| A dynamic spatiotemporal stochastic volatility model with an application to environmental risks | |
| A0948: S. Boccaletti, P. Maranzano | |
| ESG news and stock market reaction: What kind of information matters the most? | |
| A1164: A. Maruotti, P. Alaimo Di Loro | |
| Fairness in health expenditure: A bivariate bi-dimensional mixed-effects regression | |
| A1563: M. Pasic, B. Jovanovski, A. Shamsuzzoha | |
| Impact of economic growth, foreign direct investment and use of renewable energy on CO2 emissions |
| Session CO307 | Room: 236 |
| Cointegration analysis: Nonlinearity, SUR and higher integration orders | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Sebastian Veldhuis | Organizer: Sebastian Veldhuis |
| A0920: M. Wagner, O. Stypka | |
| Testing linear cointegration against smooth transition cointegration | |
| A0401: K. Reichold, M. Wagner | |
| Smooth transition cointegrating regressions: Modified nonlinear least squares estimation and inference | |
| A0788: F. Knorre, M. Wagner | |
| Fully modified OLS estimation of seemingly unrelated cointegrating polynomial regressions with common regressors | |
| A0921: S. Veldhuis, M. Wagner | |
| Integrated modified OLS estimation and inference in I(2) cointegrating regressions |
| Session CO411 | Room: 256 |
| Dynamics of digital assets - DDA | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Alla Petukhina | Organizer: Alla Petukhina |
| A1771: D.T. Pele, R.C. Bag, M. Mazurencu-Marinescu-Pele, S. Gaman, C.A. Chinie, B. Saftiuc | |
| Understanding digital assets | |
| A1781: S. Trimborn, Y. Chen, R.-B. Chen | |
| Influencers, inefficiency and fraud: The Bitcoin price discovery network under the microscope | |
| A1812: C. Hafner, A. Harvey, L. Wang | |
| Modeling and tracking bubbles | |
| A1898: M. Wunsch | |
| Decentralized investment management with constant function market makers |
| Session CO394 | Room: 257 |
| Advances in climate and energy econometrics | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Jamie Cross | Organizer: Jamie Cross |
| A1642: J. Cross | |
| Oil and the stock market revisited: A mixed functional VAR approach | |
| A1677: J. Saadaoui, V. Mignon | |
| How do political tensions and geopolitical risks impact oil prices? | |
| A1846: C. Wegener, T. Klein, R. Kruse-Becher | |
| EU ETS market expectations and rational bubbles | |
| A1849: P. Labonne, J. Cross | |
| Aggregate disagreement |
| Session CO356 | Room: 258 |
| Inflation dynamics and forecasting | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Marta Banbura | Organizer: Marta Banbura |
| A1500: M. Mogliani, F. Odendahl | |
| Density forecast frequency transformation via copulas | |
| A1516: D. Leiva-Leon, H. Le Bihan, M. Pacce | |
| Underlying inflation and asymmetric risks | |
| A1530: M. Banbura, J. Chan, B. Fu | |
| Advances in modeling time-varying trends using large VARs | |
| A1851: J. Paredes, M. Lenza, M. Banbura | |
| Forecasting inflation |
| Session CO253 | Room: 260 |
| Macroeconomic now- and forecasting | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Karin Klieber | Organizer: Karin Klieber, Niko Hauzenberger |
| A0356: T. Scheckel, F. Huber, G. Koop, M. Marcellino | |
| Stochastic block network vector autoregressions | |
| A0542: H. Mikosch, M. Daniele, S. Neuwirth | |
| An observation-driven mixed-frequency VAR model with closed-form solution | |
| A0711: T. Reinicke, M. Daniele, P. Kronenberg | |
| Transform and sparsify: Advancing macroeconomic predictions | |
| A0984: M. Daniele, P. Kronenberg, T. Reinicke | |
| Optimal predictor and transformation selection for macroeconomic forecasting using variable importance in random forests |
| Session CC511 | Room: 259 |
| Financial modelling | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Ibrahim Tahri | Organizer: CFE |
| A0910: M. Nishihara, T. Shibata | |
| The effects of a financial covenant on optimal capital structure and firm value | |
| A1807: E. Lin, C.-L. Kao, S.-C. Wu | |
| How do buys and sells interact: A copula-based PIN model with zero-inflated Poisson distributions | |
| A0221: A. Gadhi | |
| Automated predictive analysis of crude oil pricing | |
| A1227: M. Sojoudi | |
| Identifying shocks in oil futures returns curves using AR-MIDAS regression models |
| Session CC537 | Room: 261 |
| Option and stock pricing | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Robinson Kruse-Becher | Organizer: CFE |
| A0223: G. Li, J. Cao, X. Zhan, G. Zhou | |
| Betting against the crowd: Option trading and market risk premium | |
| A1577: E. Bacon, G. Gauthier, J.-F. Begin | |
| On general semi-closed-form solutions for VIX derivative pricing | |
| A1655: M. Kerkemeier | |
| Co-explosiveness of equity prices and corporate credit spreads | |
| A2000: A. Perez Martin, M.V. Ferrandez-Serrano, P. Angosto Fernandez, H. Bonet Jaen | |
| Navigating the euro capital markets amidst monetary policy tightening threats |
| Session CC491 | Room: 262 |
| Theoretical econometrics | Monday 18.12.2023 10:40 - 12:20 |
| Chair: Luca De Angelis | Organizer: CFE |
| A0388: C. Wang, M.-N. Tran, R. Kohn | |
| Realized recurrent conditional heteroskedasticity model for volatility modelling | |
| A1498: Y. Xu, G. Phillips, Y. Xu | |
| Almost unbiased variance estimation in simultaneous equation models | |
| A1740: C. Grivas, Z. Psaradakis | |
| Automated bandwidth selection for inference in linear models with time-varying coefficients | |
| A0154: P. Zadrozny | |
| Gaussian maximum likelihood estimation of static and dynamic-var factor models |
| Parallel session O: CMStatistics | Monday 18.12.2023 | 13:50 - 15:05 |
| Session EI010 (Special Invited Session) | Room: 350 |
| High-dimensional and complex data analysis | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Zhaoyuan Li | Organizer: Zhaoyuan Li |
| Session EO183 | Room: 340 |
| Recent advances in clustering and classification with missing data | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Marta Nai Ruscone | Organizer: Daniel Fernandez, Marta Nai Ruscone |
| B0226: R. Aschenbruck, G. Szepannek, A. Wilhelm | |
| Imputation strategies for clustering mixed-type data with missing values | |
| B0637: V. Audigier, N. Niang | |
| Handling missing data in clustering using multiple imputation | |
| B1023: W. van Loon, M. Fokkema, M. De Rooij | |
| Imputation of missing values in multi-view data |
| Session EO057 | Room: 348 |
| Advancements in statistical network analysis | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Jonathan Stewart | Organizer: Jonathan Stewart |
| B1237: V. Lyzinski, Z. Li, J. Arroyo, K. Pantazis | |
| Clustered graph matching for label recovery and graph classification | |
| B1835: N. Niezink | |
| Mixed-effects modeling for multiplex social networks | |
| B2002: R. Zheng, M. Tang | |
| Distributed estimation of invariant subspaces in multiple network inference |
| B0405: S. Legramanti, V. Ghidini, R. Argiento | |
| Leveraging covariates in Bayesian nonparametric clustering: An application to transportation networks | |
| B0563: A. Zito, T. Rigon, D. Dunson | |
| Bayesian nonparametric modeling of latent partitions via Stirling-gamma priors | |
| B0639: L. Alamichel, J. Arbel, G. Kon Kam King, D. Bystrova | |
| Bayesian mixture models inconsistency for the number of clusters |
| Session EO290 | Room: 352 |
| Advances in Markov chain Monte Carlo | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Chunlin Li | Organizer: Vivekananda Roy |
| Session EO284 | Room: 353 |
| Bayesian advances: Vaccine safety, mortality, nonlinear tensor regression | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Sharmistha Guha | Organizer: Sharmistha Guha |
| B1721: F. Bu | |
| Bayesian methods for vaccine safety surveillance using federated data sources | |
| B1739: Q. Wang, R. Casarin, R. Craiu | |
| A Bayesian nonlinear tensor regression | |
| B1897: J. Fuquene | |
| Bayesian methods to estimate the completeness of death registration |
| Session EO103 | Room: 354 |
| Statistical methods for modern business applications (virtual) | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Trambak Banerjee | Organizer: Trambak Banerjee |
| B1667: S. Parsaeian, A. Mehrabani | |
| Time-varying panel data models with latent group structures | |
| B1675: S. Dong, S. Li, B. Sherwood | |
| Corporate probability of default: A single-index Hazard model with multiple-link approach | |
| B1761: C. Paulson, D. Smolyak, M. Vilborg Bjarnadottir | |
| Reweighting data in penalized optimization models: An approach to maximize subgroup fairness |
| Session EO209 | Room: 355 |
| Statistical machine learning for data analytics | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Senthil Murugan Nagarajan | Organizer: Senthil Murugan Nagarajan |
| B0175: G. Baklicharov, S. Vansteelandt, C. Ley | |
| Assumption-lean quantile regression | |
| B0247: B. Francesconi, Y.-J. Chen | |
| Robustly modeling the nonlinear impact of climate change on agriculture by combining econometrics and machine learning | |
| B0271: S.M. Nagarajan | |
| Classification of imbalanced class labels with and without feature selection model |
| Session EO431 | Room: 356 |
| Recent advances in sequential detection and inferences | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Liyan Xie | Organizer: Liyan Xie |
| B0748: L. Xie | |
| Sequential change-point detection for correlation matrices | |
| B1536: H. Xu, D. Wang, Z. Zhao, Y. Yu | |
| Change point inference in high-dimensional regression models under temporal dependence | |
| B1695: R. Luo | |
| Anomaly edge detection in network data using conformal prediction | |
| B1985: Y. Jiang | |
| Multivariable time series anomaly detection using heuristic spatial temporal graph neural network |
| Session EO329 | Room: 404 |
| Applied spatio-temporal modelling | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Finn Lindgren | Organizer: Finn Lindgren |
| B0578: R. Arce Guillen, F. Lindgren, S. Muff, T. Glass, G. Breed, U. Schlaegel | |
| Accounting for unobserved spatial variation in step selection analyses of animal movement via spatial random effects | |
| B0596: M.H. Suen, M. Naylor, F. Lindgren | |
| Linearization approach for aggregated landslides data | |
| B0370: B. Pirzamanbein, J. Lindstrom | |
| Reconstruction of past human land use from pollen data and anthropogenic land cover changes |
| Session EO060 | Room: 414 |
| Statistical methods for complex data | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Thomas Verdebout | Organizer: Thomas Verdebout |
| B0191: J. Trufin, M. Denuit | |
| Autocalibration by balance correction in nonlife insurance pricing | |
| B1036: G. Bernard | |
| Multivariate sign tests for sphericity: Dealing with skewness and dependent observations | |
| B1037: M. Boucher, T. Verdebout, Y. Goto | |
| On directional runs tests and their local and asymptotic optimality properties |
| Session EO261 | Room: 424 |
| Kernel density estimation in Riemannian manifold and robust ZIP models | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Anne Francoise Yao | Organizer: Anne Francoise Yao |
| B1540: M.J. Llop, A.F. Yao, A. Bergesio | |
| Estimation for the partially linear ZIP regression model: A robust proposal | |
| B1182: M. Abdillahi Isman, W. Nefzi, S. Khardani, P.A.M. Mbaye, A.F. Yao | |
| Kernel density estimation for stochastic process with values in a Riemannian manifold | |
| B1246: A.F. Yao, V. Monsan, D.G.-A. Kouadio | |
| Kernel density estimation for continuous time processes with values in a Riemannian manifold |
| Session EO187 | Room: 442 |
| Image data modeling, transfer learning and spatial process models | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Rajarshi Guhaniyogi | Organizer: Rajarshi Guhaniyogi |
| B1307: A. Banerjee | |
| Addressing the validity of information borrowing in transfer learning | |
| B1314: A. Halder, S. Mohammed, D. Dey | |
| Bayesian variable selection in double generalized linear Tweedie spatial process models | |
| B0193: A. Scheffler | |
| A disease progression model for exponential family outcomes with application to neurodegenerative diseases |
| Session EO120 | Room: 445 |
| Causal inference: Estimation techniques and fundamental limits | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Ashkan Ertefaie | Organizer: Ashkan Ertefaie |
| B0205: A. Luedtke, I. Chung | |
| One-step estimation of differentiable Hilbert-valued parameters | |
| B0500: E. Kennedy | |
| Fundamental limits of structure-agnostic functional estimation | |
| B0555: Y. Wang | |
| Partial identification with noisy covariates: A robust optimization approach |
| Session EO211 | Room: 447 |
| Developments on functional data analysis and subgroup analysis | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Dengdeng Yu | Organizer: Bei Jiang |
| B0875: C. Li | |
| Imaging mediation analysis for longitudinal outcomes | |
| B1607: X. Li, M. Kosorok | |
| Functional individualized treatment regimes with imaging features | |
| B1874: D. Yu | |
| Functional linear regression: Linear hypothesis testing with functional response |
| Session EO058 | Room: 457 |
| High-dimensional inference for data science | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Chien-Ming Chi | Organizer: Jinchi Lv |
| B1613: Y. Uematsu, P. Jiang, T. Yamagata | |
| Revisiting asymptotic theory for principal component estimators of approximate factor models | |
| B1408: C.-M. Chi | |
| High-dimensional knockoffs inference for time series data | |
| B1371: W. Sun | |
| Online inference for tensor models |
| Session EO436 | Room: 458 |
| High-dimensional statistics for complex data | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Lu Xia | Organizer: Zhengling Qi |
| Session EO064 | Room: Virtual R01 |
| Recent topics in causal inference | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Yumou Qiu | Organizer: Yumou Qiu |
| Session EO076 | Room: Virtual R02 |
| Economic data analysis and statistical inference to unfold uncertainty | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Subir Ghosh | Organizer: Subir Ghosh |
| B1541: S. Sokullu, C. Muris, I. Botosaru | |
| Partial effects in time-varying linear transformation panel models with endogeneity | |
| B1666: R. Pinto, M. Buchinsky | |
| The economics of monotonicity conditions: Exploring choice incentives in IV models | |
| A1550: H. Kawakatsu | |
| Testing spanning in affine term structure models by least squares |
| Session EO222 | Room: Virtual R03 |
| Bayesian methods for temporal dependence in complex structures | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Matthew Heiner | Organizer: Matthew Heiner |
| B1313: X. Zheng, A. Kottas, B. Sanso | |
| Mixture modelling for temporal point processes with memory | |
| B1375: D. Dahl, R. Warr, T. Jensen | |
| Dependent modeling of temporal sequences of random partitions | |
| B1321: R. Warr | |
| Dependent random partitions by shrinking towards an anchor |
| Session EO344 | Room: Virtual R04 |
| The statistical challenges in model-based data science | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Rotem Dror | Organizer: Rotem Dror |
| B0289: S. Riezler | |
| Towards inferential reproducibility of machine learning research | |
| B1239: C. Hardmeier | |
| Dealing with uncertainty in language-based AI | |
| B1327: Y. Benjamini | |
| What is love? Describing emotions using prediction models |
| Session EC552 | Room: 227 |
| Machine learning for economics and finance | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Muriel Perez | Organizer: CFE-CMStatistics |
| B1789: J.J. Cai, R. Chen, M. Wainwright, L. Zhao | |
| Doubly high-dimensional contextual bandits: An interpretable model for joint assortment-pricing | |
| B1410: C. Liu, S. Paterlini | |
| Stock price prediction using temporal graph model with value chain data | |
| B1821: A. Teller, U. Pigorsch, C. Pigorsch | |
| Forecasting realized volatility of financial assets with limited historical data |
| Session EC555 | Room: 335 |
| Tree-based methods | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Roman Hornung | Organizer: CFE-CMStatistics |
| B1427: J. Goedhart, M. van de Wiel, T. Klausch | |
| Co-data learning for Bayesian additive regression trees | |
| B1440: M. Loecher | |
| Debiasing SHAP scores in tree ensembles | |
| B1021: M. Fokkema | |
| Fitting prediction rule ensembles with multiply-imputed data, and adaptive and relaxed lasso penalties. |
| Session EC540 | Room: 357 |
| Mixture models | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Andriette Bekker | Organizer: CFE-CMStatistics |
| B1728: M. Bee | |
| Specification and estimation of mixtures with dynamic weights | |
| B1777: S. Pal, C. Heumann | |
| Flexible multivariate mixture models: A comprehensive approach for modeling mixtures of non-identical distributions | |
| B1782: A.M. Di Brisco, R. Ascari, S. Migliorati, A. Ongaro | |
| A comprehensive R package for regression models with bounded continuous and discrete responses |
| Session EC460 | Room: 401 |
| Time series | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Qianqian Zhu | Organizer: CFE-CMStatistics |
| B1393: M. Faymonville, C. Jentsch, C. Weiss | |
| Goodness-of-fit testing for INAR models | |
| B1546: N. Zakiyeva | |
| High-dimensional functional time series prediction model solved with a mixed integer optimization method | |
| B1843: A. Braumann, J.-P. Kreiss, M. Meyer | |
| Bootstrap convergence rates for the max of an increasing number of autocovariances and -correlations under stationarity |
| Session EC475 | Room: 403 |
| Robust statistics | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Annamaria Bianchi | Organizer: CFE-CMStatistics |
| Session EC551 | Room: 444 |
| Software | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Tianxi Li | Organizer: CFE-CMStatistics |
| B1218: J. Lyrvall, R. Di Mari, Z. Bakk, J. Oser, J. Kuha | |
| multilevLCA: An R package for single-level and multilevel latent class analysis with covariates | |
| B1718: F.F. Queiroz, S. Ferrari | |
| PLreg: an R package for modeling bounded continuous data | |
| B1365: M. Signorelli | |
| Pencal: An R package for the dynamic prediction of survival with many longitudinal predictors |
| Session EC547 | Room: 446 |
| Causal inference | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Dennis Dobler | Organizer: CFE-CMStatistics |
| B1255: D. Ham, C. Doss, T. Westling | |
| Inference for a log-concave counterfactual density | |
| B1647: M. Simnacher, X. Xu, H. Park, C. Lippert, S. Greven | |
| Deep nonparametric conditional independence tests for images | |
| B1622: J. Bodik, V. Chavez-Demoulin | |
| Structural restrictions in local causal discovery: Identifying direct causes of a target variable |
| Session EC461 | Room: 455 |
| Multivariate statistics | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Marie Kratz | Organizer: CFE-CMStatistics |
| B0241: J. Bauer | |
| Hierarchical variable clustering using singular value decomposition | |
| B1455: S. Kawano, T. Fukushima, J. Nakagawa, M. Oshiki | |
| Integrative multivariate regression analysis via penalization | |
| B1803: E. Gautherat, P. Bertail, E.M. Issouani | |
| New bounds for self-normalized sums in high dimensional settings |
| Parallel session O: CFE | Monday 18.12.2023 | 13:50 - 15:05 |
| Session CO144 | Room: 236 |
| Advances in time series econometrics | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Alain Hecq | Organizer: Gianluca Cubadda, Alain Hecq |
| A0552: B. Guardabascio, G. Cubadda, S. Grassi | |
| The time-varying multivariate autoregressive index model | |
| A1249: A. Hecq, D. Velasquez-Gaviria | |
| High-order spectral estimation for mixed causal-non-causal and invertible-noninvertible (MARMA) models | |
| A0759: F. Giancaterini, G. Cubadda, A. Hecq | |
| Comparative analysis of multivariate mixed causal and non-causal process representations |
| Session CO375 | Room: 256 |
| Data Analysis and Optimization in Communication and Social Networks | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Alexander Semenov | Organizer: Alexander Semenov |
| A0570: P. Zheng | |
| A proof-of-concept study of electricity transacting platform for residential prosumers | |
| A0608: T. Pimenova, V. Kolycheva, A. Semenov, D. Grigoriev | |
| The impact of news, experts and public sentiment on art prices: An empirical analysis | |
| A1316: A. Semenov, A. Skrobotov, P. Radchenko, A. Prokhorov | |
| Change point detection in time series using mixed integer programming |
| Session CO128 | Room: 257 |
| Advances in macroeconometric methods | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Aristeidis Raftapostolos | Organizer: Aubrey Poon |
| A0975: Y. Wang | |
| Inflation target at risk: A time-varying parameter distributional regression | |
| A0924: C. Martinez Hernandez | |
| Inflation forecasting in persistent times: Revisiting the role of aggregation | |
| A0994: A. Raftapostolos, G. Koop, S. McIntyre, J. Mitchell | |
| Monthly GDP growth estimates for the US states | |
| A0616: E. Bobeica, M. Banbura, C. Martinez Hernandez | |
| What drives core inflation? The role of supply shocks |
| Session CO362 | Room: 258 |
| News and the economy | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Michele Modugno | Organizer: Michele Modugno |
| A0350: N. Kroner | |
| Inflation and attention: Evidence from the market reaction to macro announcements | |
| A0383: B. Kisacikoglu, R. Gurkaynak, M. Kerssenfischer, J. Wright | |
| News and noise shape international yield curves | |
| A0422: M. Modugno, B. Palazzo | |
| Macroeconomic news and real activity |
| Session CO391 | Room: 260 |
| Advances in risk measures estimation | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Carlos Trucios | Organizer: Carlos Trucios |
| A0224: A. Rubesam, M. Zevallos, R. Branco | |
| Forecasting realized volatility: Does anything beat linear models? | |
| A0463: H. Veiga, J.M. Marin | |
| Forecasting value-at-risk and expected shortfall: A comparison study | |
| A0693: C. Trucios | |
| Forecasting risk measures in high-dimensional portfolios |
| Session CO293 | Room: 261 |
| The macroeconomics of climate change | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Marco Maria Sorge | Organizer: Marco Maria Sorge |
| A0278: A. Sardone | |
| Net zero: distributional effects and optimal share of subsidies and transfers | |
| A1824: M.M. Pisa, F.S. Lucidi, A. Franconi | |
| Temperature forecast errors in the Euro Area | |
| A0597: M. Waldinger, M. Flueckiger, H. Rainer | |
| The power of youth Fridays for future climate protests and adults political behavior |
| Session CO205 | Room: 262 |
| Spectral analysis and long memory: Applications to macroeconomics | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Alexander Meyer-Gohde | Organizer: Alexander Meyer-Gohde |
| A1916: A. Meyer-Gohde | |
| Inflation expectations and the inflation target: A case of long memory | |
| A1924: V. Less, P. Sibbertsen | |
| Testing for multiple structural breaks in multivariate long memory regression models | |
| A1529: M. Al Sadoon | |
| The spectral approach to linear rational expectations models |
| Session CC515 | Room: 259 |
| Risk analysis | Monday 18.12.2023 13:50 - 15:05 |
| Chair: Juan-Angel Jimenez-Martin | Organizer: CFE |
| A1754: M. Hronec, J. Barunik | |
| Quantile maximizer in action | |
| A1827: J. Picek, J. Jureckova | |
| Estimation of conditional value-at-risk in linear model | |
| A0242: M.R. Nieto Delfin, L.J. Espinosa Rios | |
| Bayesian neural networks applied to credit risk |
| Parallel session P: CMStatistics | Monday 18.12.2023 | 15:35 - 17:15 |
| Session EO115 | Room: 227 |
| Computational methods for option pricing | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Diego Ronchetti | Organizer: Diego Ronchetti |
| B0186: Y. Dillschneider, R. Maurer | |
| GMM estimation of stochastic volatility models using transform-based moments of derivatives prices | |
| B0354: B. Claassen, D. Ronchetti | |
| Nonparametric estimation of non-anticipative optimization strategies | |
| B0831: J. Dalderop | |
| Efficient estimation of pricing kernels and market-implied densities | |
| B1002: P. Orlowski, M. Fournier, K. Jacobs | |
| Modeling conditional factor risk premia implied by index option returns |
| Session EO322 | Room: 335 |
| Algebraic statistics | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Carlos Amendola | Organizer: Carlos Amendola, Marta Nai Ruscone |
| B0983: O. Marigliano, E. Riccomagno | |
| Algebraic model invariants for compositional data | |
| B1187: P. Misra, L. Solus, A. Markham, D. Deligeorgaki | |
| Marginal independence structures underlying Bayesian networks | |
| B1190: B. Hollering, M. Drton, J. Wu | |
| Identifiability of cyclic linear structural equation models via algebraic matroids | |
| B0562: A. Grosdos, F. Roettger, J. Coons | |
| Huesler-Reiss extremal graphical models |
| Session EO104 | Room: 340 |
| Topics on mixture models and related models | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Konstantinos Perrakis | Organizer: Konstantinos Perrakis |
| B1222: G. Chavez Martinez, A. Agarwal, A. Khalili, E. Ahmed | |
| Sparse estimation in Markov regime-switching models | |
| B1093: J. Greve | |
| The use of Riordan arrays for the hyperparameter choice of prior distributions with consistent EPPFs | |
| B0694: Y. Zhang, J. Einbeck | |
| A multivariate response model for data with correlation structures | |
| B1074: K. Perrakis, P. Papastamoulis | |
| Bayesian finite mixtures of regressions with random covariates |
| Session EO082 | Room: 348 |
| Statistical inference for high-dimensional and network data | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Marianna Pensky | Organizer: Marianna Pensky |
| B1184: D. De Canditiis | |
| The adaptive Lasso estimator of AR(p) time series with applications to INAR(p) and Hawkes processes | |
| B1185: I. De Feis | |
| A network-constrain Weibull AFT model for biomarker discovery | |
| B1242: A. Plaksienko, C. Angelini, D. De Canditiis | |
| Jewel 2.0: An improved joint estimation method for multiple Gaussian graphical models | |
| B1636: T. Zhang | |
| Theoretical guarantees for sparse principal component analysis based on the elastic net |
| Session EO267 | Room: 350 |
| Statistical inference for functional connectivity in neuroimaging | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Simon Vandekar | Organizer: Simon Vandekar |
| B0279: B. Risk, J. Ran, B. Risk, D. Benkeser | |
| Nonparametric motion adjustment in studies of functional connectivity alterations in autistic children | |
| B0634: Y. Zhao | |
| Density-on-density regression | |
| B0655: S. Davenport | |
| FDP control in multivariate linear models using the bootstrap | |
| B0248: X. Ma, S. Kundu | |
| High-dimensional measurement error models for Lipschitz losses with application to functional connectivity |
| Session EO390 | Room: 351 |
| Bayesian models and computations for complex bio-environmental data | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Francesco Denti | Organizer: Francesco Denti |
| B0341: A. Fasano, D. Durante | |
| Posterior inference in the sequential probit model with applications to medical data | |
| B0398: S. Paganin, J. Miller | |
| Improved detection of allelic imbalance using biologically informed priors | |
| B0418: M. Russo | |
| Bayesian bi-clustering for temporally heterogeneous high-dimensional longitudinal data | |
| B0430: A. Sottosanti, D. Risso | |
| Sparse Bayesian clustering of gene expression profiles in spatial transcriptomic experiments |
| Session EO280 | Room: 352 |
| Causal discovery, image analysis, regression, and social conflicts | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Yang Ni | Organizer: Samiran Sinha, Tapabrata Maiti |
| B1293: S. Chatterjee | |
| A Bayesian framework for studying climate anomalies and social conflicts | |
| B1958: T. Ghosh | |
| A robust kernel machine framework for assessing differential expression of multi sampled single cell data | |
| B1960: K. Gregory, D. Nordman | |
| Least angle regression inference | |
| B1376: Y. Ni | |
| Causal discovery from multivariate functional data |
| Session EO138 | Room: 354 |
| Recent advances in multivariate analysis and dimension reduction | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Yeonhee Park | Organizer: Yeonhee Park |
| B0196: H. Moradi Rekabdarkolaee | |
| Dimension reduction for spatially correlated data using envelope | |
| B0180: J. Wang, L. Ma, H. Chen, L. Liu | |
| Semiparametrically efficient method for enveloped central space | |
| B1507: Z. Su, S. Chakraborty, Z. Su | |
| A comprehensive Bayesian framework for envelope models | |
| B0179: Y. Park, Z. Su, D. Chung | |
| Envelope-based partial least squares with application to cytokine-based biomarker analysis for COVID-19 |
| Session EO399 | Room: 355 |
| Recent advancements in transfer learning | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Abolfazl Safikhani | Organizer: Abolfazl Safikhani |
| B1051: H. Li | |
| Transfer learning with random coefficient ridge regression with applications in genomics | |
| B1430: L. Zhang | |
| Transfer learning with spurious correlations | |
| B1465: Z. Li, Y. Shen, J. Ning | |
| Accommodating time-varying heterogeneity in risk estimation under the Cox model: A transfer learning approach | |
| B1682: A. Safikhani | |
| Transfer learning for time series models |
| Session EO353 | Room: 356 |
| Recent advances in design of experiments | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Vasiliki Koutra | Organizer: Vasiliki Koutra |
| B0623: H. Merila | |
| Multi-fidelity Bayesian optimization in high-dimensional settings | |
| B0985: N. Stevens | |
| General additive network effect models: A framework for the design and analysis of experiments on networks | |
| B1180: Q. Liu, Y. Li, S. Yang | |
| A representative sampling method for peer encouragement designs in network experiments | |
| B1640: A. Overstall | |
| Bayesian optimal designs for misspecified models |
| Session EO074 | Room: 357 |
| Extreme value analysis | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Gilles Stupfler | Organizer: Gilles Stupfler |
| B0782: A. Daouia, S. Padoan, G. Stupfler | |
| Extreme expectile estimation for short-tailed data | |
| B0961: I. Scheffel, M. Oesting | |
| Long range dependence in extreme value analysis | |
| B1186: J. Hachem, A. Daouia, G. Stupfler | |
| A de-randomization argument for estimating extreme value parameters of heavy tails | |
| B1343: S. Padoan, S. Rizzelli, C. Dombry | |
| Asymptotic theory for Bayesian inference and prediction: From the ordinary to a conditional peaks-over-threshold method |
| Session EO085 | Room: 401 |
| Statistical theory and computation for stochastic process models | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Hiroki Masuda | Organizer: Hiroki Masuda |
| B0347: E. Guidotti, N. Yoshida | |
| Asymptotic expansion formulas for diffusion processes based on the perturbation method | |
| B0441: L. Mercuri | |
| yuima.law: A class for the mathematical description of the noise in YUIMA | |
| B0747: S. Nakakita | |
| Langevin-type sampling algorithm for non-log-concave non-smooth distributions | |
| B0916: K. Kamatani, G. Roberts, J. Bierkens | |
| Scaling of piecewise deterministic Monte Carlo for anisotropic targets |
| Session EO099 | Room: 403 |
| Innovative statistical methods for quality control | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Manuela Cazzaro | Organizer: Manuela Cazzaro, Claudio Giovanni Borroni |
| B0487: P. Qiu, X. Xie | |
| Transparent sequential learning for monitoring sequential processes | |
| B0801: G. Pandolfo, I. Cascos, B. Sinova | |
| Statistical process control and the joint monitoring of multivariate data through the zonoid region parameter depth | |
| B1142: K. Bourazas, K. Fokianos, C. Panayiotou, M. Polycarpou | |
| Online change point detection with adaptive learning for multivariate processes | |
| B0669: C.G. Borroni, M. Cazzaro, P.M. Chiodini | |
| Change-point control charts in the presence of a tail-shift of the underlying distribution |
| Session EO220 | Room: 404 |
| Optimal transport and statistics (virtual) | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Nabarun Deb | Organizer: Bodhisattva Sen |
| B0295: N. Garcia Trillos | |
| Optimal transport based denoising | |
| B0987: T. Manole, S. Balakrishnan, L. Wasserman | |
| Minimax goodness-of-fit testing in Wasserstein distance | |
| B1258: A.-A. Pooladian, V. Divol, J. Niles-Weed | |
| Minimax estimation of discontinuous optimal transport maps: The semi-discrete case | |
| B1905: N. Deb | |
| Wasserstein mirror gradient flows as the limit of the Sinkhorn algorithm |
| Session EO180 | Room: 414 |
| Recent advances in change point detection | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Likai Chen | Organizer: Likai Chen |
| B1061: X. Zhang, T. Dawn | |
| Sequential gradient descent and quasi-Newton's method for change-point analysis | |
| B1147: Y. Xie, H. Wang | |
| Non-parametric distribution-free CUSUM for online change-point detection | |
| B1158: L. Chen, M.F.C. Haddad, J. Li, H. Zou | |
| Adaptive MOSUM: Inference for change points in high-dimensional time series | |
| B1167: W. Wang | |
| Inference of many regression discontinuity estimators for panel data |
| Session EO101 | Room: 424 |
| Statistical methods for single-cell and spatial biology (virtual) | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Aaron Molstad | Organizer: Aaron Molstad |
| B1413: R. Bacher | |
| scLANE: single-cell linear adaptive negative-binomial expression testing | |
| B1466: B. Guo, L. Weber, S. Hicks | |
| Scalable count-based models for unsupervised detection of spatially variable genes | |
| B1603: Y. Ma | |
| Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics | |
| B1614: D. Risso, A. Sottosanti, S. Castiglioni | |
| Biologically-informed gene clustering for spatial transcriptomics |
| Session EO318 | Room: 442 |
| Variable selection and estimation in high dimensions (virtual) | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Emre Demirkaya | Organizer: Emre Demirkaya |
| B0425: R. Li, J. Wen, S. Yang, C.D. Wang, Y. Jiang | |
| Feature-splitting algorithms for ultrahigh dimensional quantile regression | |
| B0462: S. Shekhar, A. Ramdas | |
| Sequential change detection via backward confidence sequences | |
| B0611: L. Gao, Y. Fan, J. Lv | |
| ARK: robust knockoffs inference with coupling | |
| B0612: Y. Luo, W. Fithian, L. Lei | |
| FDR estimation for variable selection methods |
| Session EO380 | Room: 444 |
| Interpretable machine learning for scientific discovery | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Reza Abbasi Asl | Organizer: Reza Abbasi Asl |
| Session EO352 | Room: 445 |
| Modern developments in causal inference and precision medicine | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Indrabati Bhattacharya | Organizer: Indrabati Bhattacharya |
| B0282: A. Chattopadhyay, C. Morris, J. Zubizarreta | |
| Balanced and robust randomized treatment assignments: The finite selection model | |
| B0707: S. Roy | |
| Group sequential testing under instrumented difference-in-differences approach | |
| B0716: A. Chakrabortty | |
| A general framework for treatment effect estimation in semi-supervised and high dimensional settings | |
| B0978: H. Cai | |
| On heterogeneous treatment effects in heterogeneous causal graphs |
| Session EO231 | Room: 446 |
| Statistical advances in Mendelian randomization for causal inference | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Yuehua Cui | Organizer: Yuehua Cui |
| B1948: S. Burgess | |
| Phenotypic heterogeneity at drug target genes for mechanistic insights: Cis-multivariable Mendelian randomization | |
| B1280: J. Jia | |
| Mendelian randomization analysis with pleiotropy-robust log-linear models for binary outcomes | |
| B1944: T. Yang, R. Zilinskas, W. Pan, X. Shen, C. Li | |
| Inferring a directed acyclic graph of phenotypes from GWAS summary statistics | |
| B1759: Y. Cui | |
| Addressing weak instruments in one sample MR analysis with MR-SPLIT |
| Session EO423 | Room: 447 |
| Advances in high-dimensional and functional data analysis | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Marzia Cremona | Organizer: Marzia Cremona |
| B1134: A. Kenney, T. Tang, Y.S. Tan, A. Agarwal, B. Yu | |
| MDI+: a flexible random forest-based feature importance framework | |
| B1048: L. Wang, J. Zhang, J. Cao | |
| Robust Bayesian functional principal component analysis | |
| B1096: A. Pini, N. Lundtorp Olsen, S. Vantini | |
| Nonparametric local inference for functional data defined on manifold domains | |
| B0443: E. Christou, E. Solea, J. Song, S. Wang | |
| Sufficient dimension reduction for conditional quantiles for functional data |
| Session EO113 | Room: 455 |
| Statistical learning with applied functional data analysis (virtual) | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Haolun Shi | Organizer: Haolun Shi |
| Session EO340 | Room: 457 |
| New developments for high-dimensional complex structured data | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Jiaying Weng | Organizer: Jiaying Weng |
| B0452: S. Ding | |
| Sufficient dimension reduction with simultaneous region selection for high dimensional tensors | |
| B1154: P.-S. Zhong, N. Abdukadyrov, W.B. Wu, X.J. Zhou | |
| Causal inference with high-dimensional outcome variables | |
| B1157: Y. Su, S. Srivastava, D. Bandyopadhyay | |
| Scalable Bayesian joint models for proportion outcomes and informative observation times | |
| B1169: X. Kong, A. Villasante-Tezanos, S. Harrar | |
| Generalized composite multi-sample tests for high-dimensional data |
| Session EO378 | Room: 458 |
| Integrative analysis via cutting-edge machine learning tools | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Nilanjana Laha | Organizer: Nilanjana Laha |
| B0414: S. Majumder | |
| Multivariate cluster point process model | |
| B0741: R. Sun, J. Choi | |
| Bayesian variable selection for interval-censored outcomes in genetic association studies | |
| B0845: R. Burkholz | |
| Pruning deep neural networks for lottery tickets | |
| B1075: E. Elia | |
| In the pursuit of automating meta-analysis |
| Session EO271 | Room: Virtual R01 |
| Inference for high dimensional data with complex structures (virtual) | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Danna Zhang | Organizer: Danna Zhang |
| B0872: D. Dai, D. Zhang | |
| Factor-augmented regression for high dimensional time series | |
| B1031: M. Xu, D. Zhang | |
| A high dimensional Cramer-von Mises test | |
| B1046: D. Zhang | |
| Test of independence based on generalized distance correlation | |
| B1047: Z. Lou | |
| Communication-efficient distributed estimation and inference for Cox's model |
| Session EO149 | Room: Virtual R02 |
| Statistical modeling of complex data structures | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Tianxi Li | Organizer: Tianxi Li |
| B0718: Y. Lee, A. Buchanan, E. Ogburn, S. Friedman, E. Halloran, N. Katenka, J. Wu, G. Nikolopoulos | |
| Finding influential subjects in a network using a causal framework | |
| B1162: L. Feng | |
| Deep Kronecker network | |
| B1241: W. Xu, Y. Zhao, T. Li, S. Wang | |
| Supervised brain functional node and network construction related to behavior under voxel-level cognitive state fMRI | |
| B1303: S. Sengupta | |
| Two generalizable strategies for scalable inference from network data | |
| B1956: X. Tang | |
| Higher-order connectivity network for multivariate point process data |
| Session EO182 | Room: Virtual R03 |
| Graph and neural network models and related topics | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Ruiqi Liu | Organizer: Zuofeng Shang |
| B0715: M. Yuan, Z. Shang | |
| Statistical inference for community structure in weighted networks | |
| B0722: R. Liu, X. Chen, Z. Shang | |
| Statistical inference with stochastic gradient methods under $\phi$-mixing data | |
| B1058: C. Jin | |
| Variant component test for cell-type-aware analysis of RNA-seq data | |
| B1338: J. Liu | |
| Statistical inference using generative adversarial networks |
| Session EO177 | Room: Virtual R04 |
| Recent advances in empirical likelihood methods and its applications | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Qing Wang | Organizer: Qing Wang |
| B0886: J. Chen, H. Liang | |
| Global consistency of empirical likelihood | |
| B0806: Y. Zhao, B. Pidgeon | |
| Jackknife empirical likelihood methods for testing the distributional symmetry | |
| B1029: P. Han | |
| Penalized empirical likelihood method for integrating external information from heterogeneous populations | |
| B0689: S. Chen | |
| Handling nonignorable nonresponse by using semiparametric fractional imputation for complex survey data |
| Parallel session P: CFE | Monday 18.12.2023 | 15:35 - 17:15 |
| Session CO148 | Room: 236 |
| Advances in Large Spatial Models | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Deborah Gefang | Organizer: Deborah Gefang |
| A1230: T. Krisztin, P. Piribauer, C. Glocker, M. Iacopini | |
| A Bayesian SAR model with endogenous time-varying spatial weight matrices | |
| A0404: M. Krock | |
| Modeling massive highly multivariate nonstationary spatial data with the basis graphical lasso | |
| A0318: J. Lee | |
| Testing endogeneity of a spatial weight matrix in a weak spatial dynamic panel data model | |
| A0544: R. MacDonald, S. Lee | |
| Flexible basis representations for modeling high-dimensional hierarchical spatial data |
| Session CO414 | Room: 257 |
| Algorithmic investment strategies | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Robert Slepaczuk | Organizer: Pawel Sakowski, Robert Slepaczuk, Piotr Wojcik |
| A1670: P. Gradzki, P. Wojcik | |
| Edge in cryptocurrency trading: Deep learning, varied data sampling, and target labeling strategies | |
| A1969: M. Wysocki, R. Slepaczuk | |
| A comparison of quantitative finance models for hedging of options portfolio | |
| A1970: R. Slepaczuk | |
| The application of various architectures of the LSTM model in algorithmic investment strategies on BTC and S\&P500 Index | |
| A1971: P. Sakowski, R. Slepaczuk, J. Michankow | |
| Mean absolute directional loss as a new loss function for machine learning problems in algorithmic investment strategies |
| Session CO189 | Room: 258 |
| Statistics and dynamics of economic and financial markets | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Rustam Ibragimov | Organizer: Rustam Ibragimov |
| A1178: D. Ning, R. Ibragimov, M. Eling | |
| Time dynamics of cyber risk | |
| A1383: V. de la Pena | |
| On the bias of the Gini coefficient | |
| A1412: N. Abdullaev, R. Ibragimov | |
| Stylised facts of the cryptocurrency market | |
| A1505: K. Mansurov, D. Grigoriev, A. Semenov | |
| Cryptocurrency exchange simulation |
| Session CO430 | Room: 260 |
| Macroeconometrics | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Francesca Loria | Organizer: Francesca Loria |
| A0170: F. Loria | |
| Understanding growth-at-risk: A Markov-switching approach | |
| A0187: S. Mouabbi, J.-P. Renne, A. Tschopp | |
| The dynamic nature of macroeconomic risks | |
| A0272: J. Arias, J. Rubio-Ramirez, D. Waggoner, M. Shin | |
| Inference based on time-varying SVARs identified with sign and zero restrictions | |
| A1102: F. Furno, D. Giannone | |
| Nowcasting recession risk in the US and the Euro Area |
| Session CO415 | Room: 261 |
| Future of AI in finance | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Branka Hadji Misheva | Organizer: Branka Hadji Misheva |
| A1411: M. Wildi, B. Hadji Misheva | |
| A time series approach to explainability for neural nets with applications to risk-management and fraud detection | |
| A1519: M. Machado | |
| Green AI in the finance industry: Experiments with feature engineering in hybrid machine learning models | |
| A1870: K. Bolesta | |
| Efficient fraud detection with AI methods | |
| A1723: P. Lameski | |
| On using AI to make AI more transparent |
| Session CO452 | Room: 262 |
| Inflation dynamics: Linear or non-linear? | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Michele Lenza | Organizer: Michele Lenza |
| A1240: L. Fosso, G. Ascari | |
| The international dimension of trend inflation | |
| A1263: B. Hofmann, S. Eickmeier | |
| What drives inflation? Disentangling demand and supply factors | |
| A1362: G. Gitti | |
| Nonlinearities in estimation of the Phillips curve | |
| A1296: M. Lenza, I. Moutachaker, J. Paredes | |
| Density forecasts of inflation: A quantile regression forest approach |
| Session CO448 | Room: 353 |
| Specification and identification robust methods (virtual) | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Lynda Khalaf | Organizer: Lynda Khalaf |
| A1575: B. Chu | |
| A nonparametric test for change-points in volatility with weighted empirical processes | |
| A1672: T. Russell, J. Gu | |
| A dual approach to Wasserstein-robust counterfactuals | |
| A1681: F. Richard, L. Khalaf | |
| Multiple testing for asset pricing factor models | |
| A1694: B. Antoine, O. Boldea, N. Zaccaria | |
| Inference in linear models with structural changes and mixed identification strength |
| Session CC514 | Room: 256 |
| Empirical finance | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Juan-Angel Jimenez-Martin | Organizer: CFE |
| A1347: A. Ajello | |
| More than words: Twitter chatter and financial market sentiment | |
| A1531: L. Petrasek | |
| US equity announcement risk premia | |
| A1544: S. Pybis, M. Stamatogiannis, O. Henry | |
| Do not industries lead stock markets? | |
| A1747: G. Bauer, S. Gungor, J. Witmer | |
| Asymmetric information in government bond markets: Evidence from a small, open economy |
| Session CC498 | Room: 259 |
| Time series econometrics | Monday 18.12.2023 15:35 - 17:15 |
| Chair: Massimiliano Caporin | Organizer: CFE |
| A0809: F. Schirra, J. Sass, S. Schwaar | |
| A change point test for Poisson INARCH(1) processes with logistic intensity | |
| A1891: J. Bruha | |
| A sparse Kalman filter: A non-recursive approach | |
| A1896: F. Krabbe | |
| Modelling switching regimes with score-driven time series models | |
| A1589: I. Kasparis | |
| Regressions with heavy tailed weakly nonstationary processes |