KEYNOTE TALKS
| Keynote talk 1 | Tuesday 01.8.2023 | 15:10 - 16:00 | Room: 102 |
| Fusion learning: Combining inferences from diverse data sources with heterogeneous data | |||
| Speaker: R. Liu Co-authors: D. Liu, M.-G. Xie | Chair: Yan Liu | ||
| Keynote talk 2 | Thursday 03.8.2023 | 11:30 - 12:20 | Room: 102 |
| Network approaches in healthcare, business and social sciences | |||
| Speaker: M. So | Chair: Ana Colubi | ||
| Keynote talk 3 | Thursday 03.8.2023 | 17:15 - 18:05 | Room: 102 |
| Sufficient dimension reduction meets two-sample regression estimation | |||
| Speaker: M. Hirukawa | Chair: Erricos Kontoghiorghes | ||
PARALLEL SESSIONS
| Parallel session A: EcoSta2023 | Tuesday 01.8.2023 | 08:50 - 09:40 |
| Session EV316 | Room: Virtual R01 |
| Functional data analysis | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Long Nguyen | Organizer: EcoSta |
| E0263: H. Yeon, X. Dai, S. Lopez Pintado | |
| Regularized halfspace depth for functional data | |
| E0266: S. Kim, X. Dai, M. Kaiser | |
| A generalized functional linear model with spatial dependence | |
| E0729: F. Alshahrani, Z. Kaid, Z.C. Elmezouar, A. Laksaci, R.M. Almarzoqi | |
| Functional data driven financial risk management: An application to the NASDAQ Index |
| Session EI053 | Room: 604 |
| Advances in econometrics and statistics | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Donggyu Kim | Organizer: Donggyu Kim |
| E0163: M.H. Seo, Y. Liao, Y. Shin, S. Lee | |
| Fast inference for quantile regression with tens of millions of observations | |
| E0164: S. Wu, Y. Wang | |
| Reinforcement learning via nonparametric smoothing in a continuous-time stochastic setting | |
| E0890: S. Lee, S.J. Jun | |
| Identifying the effect of persuasion |
| Session EO096 | Room: 02 |
| Personalized decision-making with longitudinal data | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Yifan Cui | Organizer: Yifan Cui |
| E1275: R. Zhan, V. Syrgkanis | |
| Post-episodic reinforcement learning inference | |
| E1291: Y. Luo | |
| Dynamic assortment selection with position effects | |
| E1301: H. Cai | |
| Towards trustworthy explanation: On causal rationalization |
| Session EO011 | Room: 03 |
| Modern analytical methods for biomedical research | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Jiwei Zhao | Organizer: Jiwei Zhao |
| Session EO204 | Room: 04 |
| Advanced and practical Bayesian methods for biomedical research | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Menggang Yu | Organizer: Yuan Ji |
| E0425: Y. Li | |
| A uniform shrinkage prior in spatiotemporal Poisson models for count data | |
| E1164: J. Yin, P. Noseworthy, X. Yao | |
| External control designs to incorporate real-world evidence with adaptive information borrowing | |
| E0748: Y. Xu | |
| Statistical inference of selection coefficient from temporal allele frequencies |
| Session EO051 | Room: Virtual R02 |
| Recent advances in analysis of point process data | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Kuang-Yao Lee | Organizer: Kuang-Yao Lee |
| Session EO073 | Room: 102 |
| Spatial epidemiology | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Pei-Sheng Lin | Organizer: Pei-Sheng Lin |
| E0331: M. Kamenetsky, J. Zhu, R. Gangnon, J. Lee | |
| Regularized spatial and spatio-temporal cluster detection: Applications to breast cancer | |
| E0616: T.-H. Wen, Y.-P. Lee | |
| Understanding the spread of infectious diseases in edge areas of hotspots | |
| E0918: F.-C. Lin, S. Noble, G. Bell | |
| Minibus connectivity to brothels in Lilongwe, Malawi, and implications for STI clinic attendance |
| Session EO077 | Room: 201 |
| Nonparametric causal inference | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Nilanjana Laha | Organizer: Jason Xu |
| E0231: N. Hejazi, I. Diaz, D. Benkeser, M. van der Laan | |
| Efficient estimation of modified treatment policy effects based on the generalized propensity score | |
| E0867: L. Liu | |
| New root-n consistent, numerically stable higher-order influence function estimators | |
| E1266: N. Laha | |
| The optimal dynamic treatment regime using smooth surrogate losses |
| Session EO165 | Room: 203 |
| Recent statistical advances in biomedical sciences | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Binyan Jiang | Organizer: Yunpeng Zhao |
| E0635: X. Sun | |
| Zero-inflated smoothing spline for single-cell data | |
| E0643: X. Li, Z. Guo | |
| Robust inference for federated meta-learning | |
| E0669: Z. He | |
| Design of network-based studies to estimate individual and spillover effects and identify key influencer |
| Session EO018 | Room: 503 |
| Advances in nonparametric inference, fairness, and IV regression | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Daoji Li | Organizer: Daoji Li |
| E0998: P. Vossler, H. Elzayn, E. Black, N. Jo | |
| Estimating and implementing conventional fairness metrics with probabilistic protected features | |
| E1148: M. Sharifvaghefi | |
| Optimal invariant tests in an instrumental variables regression with heteroskedastic and autocorrelated | |
| E0953: H. Suzuki, N. Iwasa | |
| Improvement of gradient boosting using regularization and optimization algorithms | |
| E1334: E. Demirkaya, L. Gao, J. Lv, Y. Fan, J. Wang, P. Vossler | |
| Optimal nonparametric inference with two-scale distributional nearest neighbors |
| Session EO032 | Room: 506 |
| Advanced statistical learning approaches in analyzing complex modern data | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Xiwei Tang | Organizer: Xiwei Tang |
| E0474: L. Liu | |
| Innovative precision medicine methods in subgroup identification for Alzheimers disease | |
| E0632: J. Rodu, J. Rodu, X. Ma | |
| Recent advances in fast estimation of high-dimensional hidden Markov models | |
| E0704: P. Ruan | |
| A multi-use graph neural network framework for single-cell multi-omics data |
| Session EO112 | Room: 603 |
| Nonparametric methods in finance and econometrics | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Huanjun Zhu | Organizer: Weixuan Zhu |
| E1304: M. Xiaoling | |
| Bayesian nonparametric portfolio selection with rolling maximum drawdown control | |
| E0698: H. Zhu | |
| Robust M-estimation for high dimensional regression on large panel data | |
| E0772: S. Ge | |
| Non-axis aligned space partitioning |
| Session EO212 | Room: 605 |
| Topics in statistical learning | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Archer Yang | Organizer: Archer Yang |
| Session EO078 | Room: 606 |
| Recent developments in copula modeling | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Pavel Krupskiy | Organizer: Pavel Krupskiy |
| E0563: G. Geenens | |
| Towards a universal representation of statistical dependence | |
| E0639: E. Acar, K. Zhao | |
| Conditional dependence models under covariate measurement error | |
| E1040: P. Krupskiy, B. Nasri, B.N. Remillard | |
| On factor copula-based mixed regression models |
| Session EO170 | Room: 701 |
| Recent developments in degradation analysis and related topics I | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Tsai-Hung Fan | Organizer: Tsai-Hung Fan |
| E0250: Y.-S. Cheng, C.-Y. Peng | |
| Optimum test planning for heterogeneous Wiener processes | |
| E0665: S.-L. Jeng | |
| Estimating the useful life of lithium-ion battery pack based on a mixed effect degradation model | |
| E0847: Y. Huang | |
| Local influence on gamma process and trend gamma process |
| Session EO047 | Room: 702 |
| Statistics in neuroscience | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Russell Shinohara | Organizer: Russell Shinohara |
| E0176: R. Shinohara | |
| Beyond ComBat: Next-generation harmonization methods for multi-centre neuroimaging studies | |
| E0208: J. Goldsmith | |
| Arguments for the biological and predictive relevance of the proportional recovery rule | |
| E0470: E. Hector | |
| Partition learning for functional neuro connectivity |
| Session EO158 | Room: 703 |
| Advances in contemporary spatial and spatiotemporal data analysis | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Shan Yu | Organizer: Shan Yu |
| E1230: M. Kim, L. Wang, H.J. Wang | |
| Estimation and inference of quantile spatially varying coefficient models over complicated domains | |
| E1294: S. Yu, Y. Shao | |
| Identifying localized dynamic changes in large-scale spatio-temporal data through generalized nonparametric regression | |
| E1311: A. Safikhani | |
| Online change point detection in high-dimensional vector auto-regressive models | |
| E1336: X. Li, M. Kosorok | |
| Functional individualized treatment regimes with imaging features |
| Session EO081 | Room: 704 |
| Design and analysis of complex experiments: Theory and applications | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: MingHung Kao | Organizer: MingHung Kao |
| E0315: R.-B. Chen, F. Zhang, Y. Hung, X. Deng | |
| Indicator-based Bayesian variable selection for Gaussian process models in computer experiments | |
| E0750: M. Kao | |
| Optimal designs for sparse functional data | |
| E0900: F.K.H. Phoa, J.-W. Huang | |
| A systematic design construction and analysis for cost-efficient order-of-addition experiment |
| Session EO155 | Room: 705 |
| Recent advances in statistical methods and theory | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Mengyu Xu | Organizer: Mengyu Xu |
| E0597: J. Chung, Q. Zhang, C. Park | |
| Joint estimation of precision matrices for high-dimensional time series with long-memory | |
| E0674: T. Zhang, H.-H. Huang | |
| Robust sufficient dimension reduction and sufficient variable selection via distance covariance | |
| E0769: M. Xu, D. Zhang | |
| A High Dimensional Cramer-von Mises Test |
| Session EO062 | Room: 708 |
| Recent advance in neuroimaging studies | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Yi Zhao | Organizer: Yi Zhao |
| E0534: J. Kang | |
| Bayesian image mediation analysis | |
| E0657: P.V. Redondo, R. Huser, H. Ombao | |
| Measuring cross-channel information transfer in the frequency domain through spectral transfer entropy | |
| E0866: H. Shou | |
| Statistical challenges for large neuroimaging cohort studies |
| Session EO215 | Room: 709 |
| Current developments in industrial and applied statistics | Tuesday 01.8.2023 08:50 - 09:40 |
| Chair: Tsung-Jen Shen | Organizer: Tsung-Jen Shen, Chang-Yun Lin |
| Parallel session B: EcoSta2023 | Tuesday 01.8.2023 | 10:10 - 11:50 |
| Session EO183 | Room: 02 |
| Advances of high-dimensional statistics in biological and biomedical research | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Zhao Ren | Organizer: Zhao Ren |
| E0790: Y. Zhang, Q. Liu | |
| Integrative structural learning of mixed graphical models via pseudo-likelihood | |
| E0957: A. Ellingworth, W. Zhou, D. Ghosh, Z. Zhao | |
| A data adaptive nonparametric procedure to define and assess reproducibility across high-throughput studies | |
| E0487: Z. Ren | |
| Heteroskedastic sparse PCA in high dimensions | |
| E0813: Y. Xie | |
| Supervised capacity preserving mapping: A clustering guided visualization method for scRNAseq data |
| Session EO059 | Room: 03 |
| Modern statistical methods for data analysis | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Kuo-Jung Lee | Organizer: Kuo-Jung Lee |
| E0471: I.-C. Chen | |
| Marginal quantile regression for longitudinal data with time-dependent covariates and its applications | |
| E0501: J.-R. Tsai, L. Ting-I | |
| Linear measurement models with replications in independent variable | |
| E0973: C.-H. Chu | |
| Bayesian structure selection approaches for multiple binary responses via multi-task learning | |
| E1161: H. Kang, Y. Mei, I. Lyu, K. Albert, B. Boyd, B. Landman, W. Taylor | |
| Fast Bayesian whole brain connectivity estimation by GPU-enhanced Gaussian processes |
| Session EO180 | Room: 04 |
| Recent advances in the analysis of censored data | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Feng-Chang Lin | Organizer: Sy Han Chiou |
| Session EO012 | Room: Virtual R01 |
| Spatial statistics | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Kapil Gupta | Organizer: Soutir Bandyopadhyay |
| E0517: K. Gupta, S. Deb | |
| Efficient divide-and-conquer approach for spatio-temporal modeling of real estate data | |
| E0518: R. Guhaniyogi | |
| Bayesian multi-modal data integration | |
| E0519: I. Sahoo | |
| Estimating atmospheric motion winds from satellite image data using space-time drift models | |
| E0520: S. Dutta, D. Mondal | |
| Matrix-free conditional simulations of Gaussian fields on a regular lattice |
| Session EO187 | Room: Virtual R02 |
| Statistical methods in health research | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Jeong Hoon Jang | Organizer: Jeong Hoon Jang |
| E0494: I.-Y. Kwak | |
| Proformer: A hybrid macaron transformer model predicts expression values from promoter sequences | |
| E0548: C. Chang, J. Heo, J. Kang, T. Kim | |
| Federated statistical learning with differential privacy | |
| E0574: M.J. Ha | |
| A unified mediation analysis framework for integrative cancer proteogenomics with clinical outcomes | |
| E0594: J.H. Jang | |
| Assessing intra- and inter-method agreement of functional data |
| Session EO114 | Room: 102 |
| Network, graphical model and mixture models | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Wenlin Dai | Organizer: Wenlin Dai |
| E0292: Z. Feng, X. Chen, H. Peng | |
| Estimation and order selection for multivariate exponential power mixture models | |
| E0395: N. Zhang, M. Nanshan, J. Cao | |
| A joint estimation approach to sparse additive ordinary differential equations | |
| E0403: Y. Wang | |
| Combining smoothing spline with conditional Gaussian graphical model for density and graph estimation | |
| E1046: K. Yang, L. Qin, T. Tong, W. Guo, S. Zhao | |
| A comparison of two inconsistency detecting models for network meta-analysis |
| Session EO154 | Room: 201 |
| Advances in semiparametric methods for causal inference | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Kendrick Li | Organizer: Kendrick Li, Xu Shi |
| E0862: C. Park, E. Tchetgen Tchetgen | |
| Universal difference-in-differences | |
| E1103: T. Ye | |
| Debiased multivariable Mendelian randomization | |
| E1105: K. Li, X. Shi, W. Miao | |
| A novel continuum-of-resistance model and doubly robust for nonresponse adjustment with callback data | |
| E1127: W. Miao | |
| Introducing the specificity score: A measure of causality beyond P value |
| Session EO189 | Room: 203 |
| Recent advances in network analyses | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Hongmei Zhang | Organizer: Hongmei Zhang, Xianzheng Huang |
| E0743: X. Huang, H. Zhang | |
| Detecting responsible nodes in differential Bayesian networks | |
| E0884: E. Ogburn | |
| Causal inference for social network data | |
| E0916: H. Zhang | |
| Comparing dependent directed Gaussian networks | |
| E0999: M. Leung | |
| Unconfoundedness with network interference |
| Session EO242 | Room: 503 |
| Bayesian modeling and computation with behavioral and social applications | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Xiaojing Wang | Organizer: Xiaojing Wang |
| E1277: E. Conlon, Z. Wei | |
| Parallel Markov chain Monte Carlo for Bayesian hierarchical models with big data, in two stages | |
| E1285: X. Wang, J. Sun, L. Yang, M.-H. Chen | |
| Variable selection in dynamic item response theory models via Bayes factors with a single MCMC output | |
| E1302: P. Zhang | |
| Variational Bayesian inference for bipartite MMSBM with applications to collaborative filtering | |
| E1303: W. Wu, Z. Hong | |
| Managers positive facial expressions and earnings quality |
| Session EO104 | Room: 506 |
| Trustworthy machine learning methods and applications | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Jie Ding | Organizer: Xuan Bi |
| E0178: L. Tang | |
| RISE: Robust individualized decision learning with sensitive variables | |
| E0920: E. Lock | |
| Integrative regression and factorization of bidimensionally linked matrices | |
| E0924: X. Tang | |
| Continuous-time recommender system for implicit feedback | |
| E0980: G. Wang, J. Ding, Y. Yang | |
| Pruning deep neural networks from a sparsity perspective |
| Session EO207 | Room: 603 |
| Change points detection for time series | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Likai Chen | Organizer: Likai Chen |
| E0378: L. Chen, J. Li | |
| Adaptive two way change points detection | |
| E0675: R. Wang, X. Shao, Y. Zhang | |
| Adaptive testing in high dimension | |
| E0939: W.B. Wu | |
| Change point analysis with irregular signals: When did the COVID-19 pandemic start? | |
| E0165: S. Chib | |
| Change points detection in VAR models |
| Session EO009 | Room: 604 |
| Recent advances in financial econometrics | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Toshiaki Watanabe | Organizer: Toshiaki Watanabe |
| E0234: C.W.-S. Chen, H.-Y. Hsu, T. Watanabe | |
| Tail risk forecasting of realized volatility CAViaR models | |
| E0571: J. Nakajima | |
| Time-varying parameter local projections with stochastic volatility | |
| E0647: M. Takahashi | |
| Analyzing intraday variation in price impact: A Bayesian SVAR approach with stochastic volatility estimation | |
| E0760: T. Ishihara | |
| A realized multi-factor regression model with realized stochastic volatility |
| Session EO239 | Room: 605 |
| Analysis challenges for complex featured data | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Wenqing He | Organizer: Wenqing He |
| E0434: Y. Sun, Q. Shou, P. Gilbert, F. Heng, X. Qian | |
| Semiparametric additive time-varying coefficients model for longitudinal data with censored time origin | |
| E1193: G. Yi | |
| Semiparametric methods for left-truncated and right-censored survival data with covariate measurement error | |
| E1194: W. He | |
| Feature Screening with Large Scale and High Dimensional Censored Data | |
| E1178: X. Zhao, X. Zhou, W. Su, C. Liu, Y. Jiao, J. Huang | |
| Deep generative estimation of conditional survival function |
| Session EO123 | Room: 606 |
| Nonstationary and high-dimensional time series: Solutions for challenges | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Ansgar Steland | Organizer: Ansgar Steland |
| E0816: K. Yata, A. Ishii, M. Aoshima | |
| Estimation of the strongly spiked eigenstructure in high-dimensional settings | |
| E0952: A. Steland | |
| Inference and change-point testing of high-dimensional spectral density matrices: Beyond spectral averages | |
| E0987: J. Vogler, V. Golosnoy | |
| Unrestricted maximum likelihood estimation of multivariate realized volatility models | |
| E0589: J. Hirukawa | |
| Rank tests for randomness against time-varying MA alternative |
| Session EO172 | Room: 701 |
| Recent developments in degradation analysis and related topics II | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Chien-Yu Peng | Organizer: Tsai-Hung Fan |
| E0930: I.-C. Lee | |
| Planning of an accelerated degradation test | |
| E0959: L. Huwang | |
| A new Phase II change-point detection control chart for monitoring and diagnostics of linear profiles | |
| E0995: Y.-F. Wang | |
| Analysis of zero-increment degradation data | |
| E1317: Y.-S. Dong, T.-H. Fan, C.-Y. Peng | |
| The first-passage-time moments for Hougaard Process and its Birnbaum-Saunders approximation |
| Session EO205 | Room: 702 |
| Topics in microbiome data analysis | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Julia Fukuyama | Organizer: Julia Fukuyama |
| E0633: M. Valdez Cabrera | |
| Statistical methods to analyze phylogenetic trees with non-identical leaf sets | |
| E0869: T. Randolph, Y. Wang, A. Shojaie, P. Knight, J. Ma | |
| Generalized matrix decomposition regression and inference for two-way structured data | |
| E0913: D. Mondal, A. Mukherjee | |
| Distance-based run tests from complex high-dimensional data | |
| E0857: K. Sankaran | |
| Logistic-normal multinomial mediation analysis of microbiome community profiles |
| Session EO070 | Room: 703 |
| Statistical analysis for data with complex structures | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Binyan Jiang | Organizer: Jing Zeng, Binyan Jiang |
| E0298: J. Zhang | |
| Directed community detection with network embedding | |
| E0386: B. Zhang | |
| Factor modelling for clustering high-dimensional time series | |
| E0432: Y. Wu | |
| Longitudinal elastic shape analysis of surfaces | |
| E1144: B. Jiang | |
| A two-way heterogeneity model for dynamic networks |
| Session EO093 | Room: 704 |
| Advanced developments in complex data analysis and experimental design | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Ming-Chung Chang | Organizer: Ming-Chung Chang |
| E0221: S.-H. Huang, K. Shedden, H.-W. Chang | |
| Inference for the dimension of a regression relationship using pseudo-covariates | |
| E0222: S.-F. Tsai | |
| Generating optimal order-of-addition two-level factorial designs | |
| E0645: C.-L. Sung | |
| Functional-input Gaussian processes with applications to inverse scattering problems | |
| E0352: J. Liu | |
| Sufficient dimension reduction for Poisson regression |
| Session EO079 | Room: 705 |
| Statistical challenges for complex brain signals and images | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Michele Guindani | Organizer: Michele Guindani |
| Session EO197 | Room: 708 |
| Statistical methodologies for infinite dimensional data | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Subhra Sankar Dhar | Organizer: Subhra Sankar Dhar |
| E0641: D. Kurisu, T. Otsu | |
| Model averaging for global Frechet regression | |
| E0811: S. Bhar | |
| Finite-dimensional realizations for stochastic PDEs | |
| E0863: J. Li | |
| Statistical inference for mean function of longitudinal imaging data over complicated domains | |
| E0825: S. Bhattacharjee, H.-G. Mueller | |
| Concurrent object regression |
| Session EO181 | Room: 709 |
| Statistical learning on complex data | Tuesday 01.8.2023 10:10 - 11:50 |
| Chair: Ting Li | Organizer: Ting Li |
| Parallel session C: EcoSta2023 | Tuesday 01.8.2023 | 13:20 - 15:00 |
| Session EI003 | Room: 102 |
| New developments of Bayesian econometrics and statistics | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Cathy W-S Chen | Organizer: Cathy W-S Chen |
| E0153: T. Watanabe, J. Nakajima | |
| Time-varying parameter heterogeneous autoregressive model with stochastic volatility | |
| E0154: R. Gerlach, V. Tendenan, C. Wang | |
| The Bayesian lasso for variable selection of realized measures in a realized EGARCH model | |
| E0155: Y. Omori, N. Awaya | |
| Particle rolling MCMC with double-block sampling |
| Session EO044 | Room: 02 |
| High dimensional data analysis, copula estimation, and genetic statistics | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Su-Yun Huang | Organizer: Su-Yun Huang |
| E0463: X. Dou | |
| A parameterized empirical beta copula | |
| E0464: C.-H. Kao | |
| An R package for QTL mapping and hotspot detection | |
| E0190: H. Hung, S.-Y. Huang | |
| On the efficiency-loss free ordering-robustness of product-PCA | |
| E0408: S.-H. Wang, K. Yata | |
| Contrastive principal component analysis in high dimension low sample size |
| Session EO057 | Room: 03 |
| The Stein method, limit theorems and applications | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Zhuosong Zhang | Organizer: Xiao Fang |
| E0373: Z. Zhang | |
| BerryEsseen bounds for generalized U-statistics | |
| E0561: K. Balasubramanian | |
| Non-asymptotic rates for random forest prediction intervals via Stein's method | |
| E0693: H. Yamagishi, N. Yoshida, Y. Mishura | |
| Asymptotic expansion of an estimator for the Hurst coefficient | |
| E1065: S. Liu, X. Fang, Q.-M. Shao | |
| Cramer-type moderate deviation for quadratic forms with a fast rate |
| Session EO072 | Room: Virtual R01 |
| Recent advances in Gaussian process theory and applications | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Cheng Li | Organizer: Cheng Li |
| E0309: Y. Zhu | |
| Radial neighbors for provably accurate scalable approximations of Gaussian processes | |
| E0318: F. Bachoc | |
| Maximum likelihood estimation for Gaussian processes under inequality constraints | |
| E0427: N. Wu, D. Dunson | |
| Inferring manifolds from noisy data using Gaussian processes | |
| E0500: S. Srivastava | |
| Distributed Bayesian varying coefficient modeling using a Gaussian process prior |
| Session EO225 | Room: 503 |
| Advances in Bayesian nonparametrics and model-based clustering | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Beatrice Franzolini | Organizer: Beatrice Franzolini |
| E0630: B. Betancourt | |
| Adaptive prior distributions for record linkage tasks | |
| E0680: F. Gaffi, D. Durante, A. Lijoi, I. Pruenster | |
| Partially exchangeable stochastic block models for multilayer networks | |
| E0360: M. Catalano | |
| Measuring the impact of the prior in Bayesian nonparametrics via optimal transport | |
| E0433: A. Guglielmi | |
| Bayesian clustering of high-dimensional data via latent repulsive mixtures | |
| E0505: A. Cremaschi, M. De Iorio, T. Wertz | |
| Repulsion, chaos and equilibrium in mixture models |
| Session EO195 | Room: 506 |
| Recent advances in statistical modeling | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Eftychia Solea | Organizer: Eftychia Solea |
| E0283: J. Virta, A. Artemiou | |
| Poisson PCA for matrix count data | |
| E0457: K. Kim | |
| On sufficient graphical model | |
| E0598: A.-N. Soale, Y. Dong, C. Chen | |
| A concave pairwise fusion approach to multiresponse regression clustering | |
| E0808: S.S. Dhar, D. Mukherjee | |
| Nonparametric estimation for IID paths of SDE perturbed by Levy noise |
| Session EO074 | Room: 603 |
| Fiscal and monetary policies | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Etsuro Shioji | Organizer: Etsuro Shioji |
| E0661: H. Morita, T. Ono, R. Matsumoto | |
| Central bank information effects in Japan: The role of uncertainty channel | |
| E0371: A. Rogantini Picco, L. Melosi, F. Zanetti, H. Morita | |
| The signaling effects of fiscal announcements | |
| E0684: T. Sekine | |
| Dark matter of Japanese government bonds | |
| E0496: E. Shioji | |
| Yield curve control under attack: Where do the pressures come from? |
| Session EO196 | Room: 604 |
| Recent advances in methodological econometrics | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Chu-An Liu | Organizer: Chu-An Liu |
| E0685: Y.-C. Chen | |
| Long memory and structural breaks in testing the implied-realized volatility relation | |
| E0305: C.-A. Liu, T.-C. Lin | |
| Model averaging prediction for possibly nonstationary autoregressions | |
| E0613: Y.-M. Yen, M. Huber, Y.-C. Hsu | |
| Robust estimation of the quantile mediation treatment effect with machine learning | |
| E0453: H.H. Kwok | |
| Nonlinear least squares, model selection, and model averaging for social interaction models |
| Session EO086 | Room: 605 |
| Statistical theory for stochastic processes | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Teppei Ogihara | Organizer: Teppei Ogihara |
| E0389: T. Ogihara | |
| Asymptotically efficient estimation for diffusion processes with nonsynchronous observations | |
| E0526: Y. Uehara, L. Mercuri, H. Masuda | |
| Quasi-likelihood analysis for Student-Levy regression | |
| E0610: T. Takabatake | |
| Asymptotically efficient estimation for mixed fractional Brownian motion under high-frequency observations | |
| E0806: F. Chen | |
| Estimating Hawkes processes from observations of a sample path at discrete times points |
| Session EO075 | Room: 606 |
| Developments in time series modelling and inference | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Feiyu Jiang | Organizer: Feiyu Jiang |
| E0437: Y. Lin, Y. Tu | |
| Transformed cointegration models with partially linear additivity | |
| E0627: X. Yu, M. Kejriwal, L. Nguyen | |
| Multistep forecast averaging with stochastic and deterministic trends | |
| E0510: C. Yu, K. Zhu, F. Jiang, D. Li | |
| Matrix GARCH model: Inference and applications | |
| E0710: K. Song | |
| Estimation based on martingale difference divergence |
| Session EO111 | Room: 701 |
| Network data analysis | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Frederick Kin Hing Phoa | Organizer: Frederick Kin Hing Phoa |
| E0755: C.-H. Yeang | |
| Inferring associations along the causal chains in a network | |
| E0819: T.-J. Yen | |
| Link prediction by exploring common neighborhoods | |
| E0826: W.-C. Liu | |
| Quantifying biodiversity from network perspectives | |
| E1010: C.-H. Huang, F.K.H. Phoa | |
| A uniform placement of alters on spherical surface for ego-centric network with community structure and alter attributes |
| Session EO064 | Room: 702 |
| Statistical models for complex brain imaging data | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Shuo Chen | Organizer: Shuo Chen |
| E0253: X. Luo, Y. Zhao, B. Caffo, B. Wang | |
| Covariance outcome modelling via covariate assisted principal regression | |
| E0312: S. Simpson | |
| Regression frameworks for brain network distance metrics | |
| E0672: H.-H. Huang | |
| Statistical modeling for positronium lifetimeimage reconstruction using time-of-flight positron emission tomography | |
| E0859: D. Hong | |
| Graph neural network for fMRI and EEG brain data analysis |
| Session EO056 | Room: 703 |
| Recent developments in design of experiments | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Jian-Feng Yang | Organizer: Min-Qian Liu |
| E0191: F. Sun | |
| Group-orthogonal subsampling for big data linear mixed models | |
| E0192: X. He | |
| Efficient Kriging using designs with low fill distance and high separation distance | |
| E0195: Y. Tang | |
| Schematic array and its modification | |
| E0206: J.-F. Yang | |
| The order-of-addition experiments on the adjacency relationship |
| Session EO121 | Room: 704 |
| Skew distributions on the circle and their applications | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Tomoaki Imoto | Organizer: Tomoaki Imoto |
| E0450: Y. Miyata, T. Shiohama, T. Abe | |
| A cylindrical hidden Markov model based on skewed circular distributions | |
| E0504: Y. Tsuruta | |
| Data-based bin width selection for rose diagram | |
| E0609: T. Imoto | |
| New family of a toroidal distribution whose marginal and conditional distributions are skewed | |
| E0792: H. Ogata, T. Shiohama | |
| A skew transition distribution modeling for higher-order circular Markov processes |
| Session EO238 | Room: 705 |
| Spatial statistics | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Debashis Mondal | Organizer: Debashis Mondal |
| E0874: S. Chatterjee, S. Sharma | |
| A graph neural network approach for spatial statistical modeling | |
| E0880: S. Mukherjee, Z. Niu, B. Bhattacharya, G. Michailidis, S. Halder | |
| High dimensional logistic regression under network dependence | |
| E0903: K. Khan | |
| Spatial confounding in spatial linear mixed models | |
| E0909: X. Chang | |
| Additive dynamic models for correcting numerical model outputs |
| Session EO240 | Room: 708 |
| Advances in functional data analysis and their applications | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Hidetoshi Matsui | Organizer: Hidetoshi Matsui |
| E0497: T. Wakayama, S. Sugasawa | |
| Spatiotemporal factor models for functional data with application to population map forecast | |
| E0815: Y. Terada, H. Matsui | |
| On smoothing for spatial functional data | |
| E0843: M. Yamamoto, T. Anzai, K. Takahashi | |
| A functional generalized additive model-based scan statistic for disease cluster detection | |
| E0849: Y. Araki | |
| Functional mixture cure model and its application |
| Session EO166 | Room: 709 |
| High-dimensional/spatial time series analysis: Theory and applications | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Yasumasa Matsuda | Organizer: Yasumasa Matsuda |
| E0689: K. Sawaya, Y. Uematsu, M. Imaizumi | |
| Estimation of single index models in moderately high dimension | |
| E0692: R. Dai, Y. Uematsu, Y. Matsuda | |
| Estimation of large covariance matrices with mixed factor structure | |
| E0818: S.I.-M. Ko | |
| Asset pricing with co-search interaction | |
| E0694: Y. Matsuda, R. Iwafuchi | |
| Deep learning for multivariate volatility forecasting in high-dimensional financial time series |
| Session EC321 | Room: 04 |
| Multi-state and Cox models | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Russell Shinohara | Organizer: EcoSta |
| E0233: W.W. Wong, Z. Feng | |
| A Bayesian approach for chronic hepatitis C prevalence estimation to improve the accuracy of economic evaluation | |
| E0289: J. Kim | |
| Risk factors and transitional probability of clinical events in Korean CKD patients using the multi-state model | |
| E1196: C.-C. Chen, P.-F. Su | |
| Tensor association test in Cox regression model | |
| E1199: J.-Y. Hung, P.-F. Su | |
| Synthesizing auxiliary subgroup restricted mean survival information to obtain efficient estimation for Cox model |
| Session EC261 | Room: 201 |
| Methodological statistics and econometrics | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Tadao Hoshino | Organizer: EcoSta |
| E0276: N. Stegehuis, F. Blasques | |
| A score-driven filter for time-varying regression models with endogenous regressors | |
| E0362: Z. Li | |
| Model selection in panel data model with large number of fixed effects | |
| E1258: H. Klyne, R.D. Shah | |
| Doubly robust estimation of average partial effects | |
| E0516: T. Kaji, J. Cao | |
| Assessing heterogeneity in treatment effects |
| Session EC329 | Room: 203 |
| Time series I | Tuesday 01.8.2023 13:20 - 15:00 |
| Chair: Kaiji Motegi | Organizer: EcoSta |
| E0328: C.T. Ng, Y. Wu, Y. Li | |
| Threshold models for high-dimensional nonlinear time series | |
| E1158: Y. Zhang | |
| Measuring accordance movement between time series by Kendalls tau | |
| E0369: C.Y. Yau | |
| Burn-in selection in simulating time series | |
| E1322: M. Guo | |
| Forecasting and change point test for nonlinear heteroscedastic time series based on support vector regression |
| Parallel session E: EcoSta2023 | Tuesday 01.8.2023 | 16:30 - 18:35 |
| Session EV257 | Room: 701 |
| Financial econometrics (virtual) | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Toshiaki Watanabe | Organizer: EcoSta |
| E1035: Y. Rao | |
| Uncertainty and volatility: A Markov-switching GARCH-MIDAS approach | |
| E1250: R. Bouillot, B. Candelon, I. Kynigakis | |
| Real-time indicator of financial fragmentation in the euro area | |
| E1052: L. Garcia-Jorcano, M. Caporin, J.-A. Jimenez-Martin | |
| Diversifying risk parity portfolios with high-frequency principal components | |
| E1252: J.-B. Hasse, S. Siagh, C. Lecourt | |
| Institutional stock-bond portfolios rebalancing and financial stability | |
| E0200: F. Loria | |
| Understanding growth-at-risk: A Markov-switching approach |
| Session EO138 | Room: 02 |
| Learning methods for latent structures | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Long Nguyen | Organizer: Long Nguyen |
| E0350: M.-N. Tran, P. Tseng, R. Kohn | |
| Particle variational Bayes | |
| E0489: Y. Wang | |
| Harnessing geometric signatures in causal representation learning | |
| E0695: N.P.M. Ho | |
| Convergence rates for softmax gating Gaussian mixtures of experts | |
| E0739: P. De Blasi, M.F. Gil-Leyva Villa | |
| Gibbs sampling for mixtures in order of appearance: The ordered allocation sampler | |
| E0891: B. Aragam | |
| Difficulties and nonstandard minimax rates in nonparametric latent variable models and representation learning |
| Session EO148 | Room: 03 |
| Innovative design and analysis methods for optimizing healthcare | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Nina Deliu | Organizer: Nina Deliu |
| E0741: X. Liu, N. Deliu, B. Lauren, B. Chakraborty | |
| Dealing with zero-inflated count data in mobile health | |
| E0723: M.S. Tackney | |
| Missing data: A key challenge for digital outcomes in clinical trials | |
| E0766: T. Burnett | |
| Bayes optimal decision-making in adaptive enrichment clinical trials | |
| E0754: X. Wang, N. Deliu, Y. Narita, B. Chakraborty | |
| SMART-EXAM: Incorporating participants welfare into sequential multiple assignment randomized trials | |
| E0858: C. Chiavenna, F. Trentini, C.R. Borriello, M. Ercolanoni, G. Preziosi, P. Colacioppo, D. Cereda, A. Melegaro | |
| Unravelling timing and determinants of childhood vaccination: The Italian case |
| Session EO234 | Room: 04 |
| Recent advancements in reliability and quantile modeling | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Tony Sit | Organizer: Tony Sit |
| E0965: M.H. Ling | |
| On reliability analysis of one-shot device testing data with defects | |
| E1125: T. Sit | |
| On interquantile smoothness of censored quantile regression with induced smoothing | |
| E1306: J. Chen | |
| The gender wage gap over the life cycle: Evidence from Japan | |
| E1307: C.W. Chu, T. Sit | |
| Censored interquantile regression model with time-dependent covariates | |
| E1323: P.S.B. Chan | |
| Statistical inference for lifetimes of one-shot devices with gamma frailty components |
| Session EO094 | Room: Virtual R01 |
| Extreme value analysis for complex data | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Gilles Stupfler | Organizer: Gilles Stupfler |
| E0824: J. Hachem, G. Stupfler, A. Daouia | |
| A de-randomization argument for estimating extreme value parameters of heavy tails | |
| E0873: M. Oesting, J. Lederer | |
| Extremes in high dimensions: Methods and scalable algorithms | |
| E0892: P. Hubner, J. Hambuckers | |
| Hedge funds systemic risks: Which factors matter? | |
| E0948: G. Stupfler, A. Daouia, A. Usseglio-Carleve | |
| Inference for extremal regression with dependent heavy-tailed data | |
| E0990: M. Schiavone, S. Padoan, S. Rizzelli | |
| Marginal expected shortfall inference under multivariate regular variation |
| Session EO226 | Room: Virtual R02 |
| Asymptotic statistics for stochastic processes | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Masayuki Uchida | Organizer: Masayuki Uchida |
| E1080: N. Yoshida | |
| Quasi-likelihood analysis and estimation for a degenerate diffusion process | |
| E0872: K. Kamatani | |
| Scaling limit of Markov chain/process Monte Carlo methods | |
| E0351: M. Uchida, Y. Tonaki, Y. Kaino | |
| Parametric estimation for discretely observed linear parabolic SPDEs in two space dimensions | |
| E1026: M. Trabs, R. Altmeyer, F. Hildebrandt | |
| Parameter estimation for linear SPDEs: Discrete observations within the local approach |
| Session EO063 | Room: 102 |
| Emerging statistical approaches to improve the development of cultivars | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Hiroyoshi Iwata | Organizer: Hiroyoshi Iwata, Reka Howard |
| E0788: A. Onogi | |
| A Bayesian model for genomic prediction using metabolic networks | |
| E1187: H. Iwata, T.-S. Chen, C. Sato, M. Yamasaki, C.H. Kim, A. Abe, H. Shimono | |
| Bayesian optimization of genotype and environment interaction | |
| E1190: K. Hamazaki, H. Iwata, T. Mary-Huard | |
| Development of a novel GWAS method to detect QTL effects interacting with discrete and continuous genetic architecture | |
| E1219: G. Morota | |
| Quantitative genetic analysis of metabolites in rice | |
| E1221: R. Howard, S. Ray, D. Jarquin | |
| Comparing artificial-intelligence techniques with parametric prediction models for predicting soybean traits |
| Session EO247 | Room: 503 |
| Inference and prediction in Bayesian nonparametrics | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Marta Catalano | Organizer: Marta Catalano |
| E0985: M.F. Gil-Leyva Villa, R. Mena, P. De Blasi | |
| Bayesian nonparametric inference by means of stick-breaking priors with dependent lenght variables | |
| E0364: M. Beraha | |
| Random measure priors in Bayesian frequency recovery from sketches | |
| E0687: Y. Kim | |
| Bayesian analysis for functional ANOVA model | |
| E0778: A. Lijoi, F. Gaffi, I. Pruenster | |
| Nonparametric priors with fixed mean distributions | |
| E0367: G. Rebaudo, F. Ascolani, A. Lijoi, G. Zanella | |
| Clustering consistency with Dirichlet process mixtures |
| Session EO176 | Room: 506 |
| Mathematics of data science | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Dingxuan Zhou | Organizer: Dingxuan Zhou |
| E0966: J. Cai | |
| SStaGCN: Simplified stacking based graph convolutional networks | |
| E1004: X. Zhou | |
| Value-gradient based formulation of optimal control problem and machine learning algorithm | |
| E1061: S.-B. Lin | |
| Lifting the veil: Unlocking the power of depth in Q-learning | |
| E1056: D. Zhou | |
| Theory of structured deep neural networks | |
| E1062: L. Shi, Z. Zhang, D. Zhou | |
| Classification with deep neural networks |
| Session EO036 | Room: 603 |
| Current developments in quantitative finance | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Rogemar Mamon | Organizer: Rogemar Mamon |
| E0608: H. Xiong, R. Xu, W. Jiang, R. Mamon | |
| An enhanced neural network approach for agricultural index insurance design | |
| E0911: Y. Zhao | |
| Optimal commissions and subscriptions in mutual aid platforms | |
| E1074: M. Rodrigo | |
| Pricing formulas for perpetual American options with general payoffs | |
| E1101: T.K. Siu | |
| Bayesian nonlinear expectation for time series modelling and its application to Bitcoin | |
| E1049: R. Mamon | |
| A signal-processing approach in cyber risk valuation |
| Session EO026 | Room: 604 |
| Bayesian computation for complex models | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: David Nott | Organizer: David Nott |
| E0255: R. Laoiza Maya, D. Nibbering | |
| Efficient variational approximations for state space models | |
| E0441: X. Tong | |
| Sampling with constraints | |
| E0549: C. Drovandi, J. Bon, D. Nott, D. Warne | |
| Bayesian score calibration for approximate models | |
| E0550: D. Han, D. Han, K. Lee, Y. Chung, T. Choi, G. Kobayashi | |
| Semiparametric Bayesian two-stage meta-analysis for association between ambient temperature and new cases of COVID-19 | |
| E0962: M. Quiroz, T. Goodwin, R. Kohn | |
| Fast Bayesian estimation of dynamic linear regression models for semi long memory time series |
| Session EO089 | Room: 605 |
| Recent advances in time series modeling | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: George Michailidis | Organizer: George Michailidis |
| E0666: S. Karmakar | |
| Inference for nonstationary timeseries using optimal Gaussian approximation with explicit construction | |
| E0702: Y.-C. Hung | |
| Nonpivotal Granger causality tests based on vector autoregressive models | |
| E0804: A. Kaul | |
| Inference on the change point under a high dimensional covariance shift | |
| E0850: S. Trimborn, K. Zhang | |
| Influencer detection in market sectors via sparse network analysis | |
| E0895: G. Michailidis | |
| A general framework for network autoregressive processes |
| Session EO076 | Room: 606 |
| Progress in learning and modelling of complex time series and spatial data | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Zudi Lu | Organizer: Zudi Lu |
| E0384: Z. Lu, L. Wang, M. Kyriakou | |
| Estimation of threshold dynamic regression for cross-sectional dependent panel time series | |
| E0479: F. Ge, R. Peng, Z. Lu | |
| Generalising dynamic semiparametric averaging forecasting for time series with discrete-valued response | |
| E0524: F. Akashi | |
| Robust reduced rank estimation for low-rank vector AR models | |
| E0658: A. Gupta, M.H. Seo | |
| Robust inference on infinite and growing dimensional time series regression | |
| E0731: S. Wu, Z. Lu | |
| Predictive models for time series by deep structured learning |
| Session EO020 | Room: 702 |
| Multivariate problems for structured dependent data I | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Matus Maciak | Organizer: Michal Pesta, Matus Maciak |
| E0418: S. Hudecova | |
| Semi-continuous time series with volatility clustering | |
| E0845: C. Pretorius, H. Roodt | |
| Self-normalising change-point detection procedures for high-dimensional data | |
| E0291: M. Pesta, M. Huskova | |
| Regime changes, I-phenomena, and unsupervised learning | |
| E0768: I. Mizera | |
| Hockey is a cruel game: Empirical Bayes woes in predicting productivity of hockey players | |
| E0290: J. Kalina | |
| Testing exchangeability of multivariate distributions |
| Session EO122 | Room: 703 |
| Spatial and spatio-temporal methods | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Hsin-Cheng Huang | Organizer: Hsin-Cheng Huang |
| E0535: N.-J. Hsu, C.-C. Lin | |
| Changes in extreme rainfall in Taiwan | |
| E0506: Y.-S. Chin, N.-J. Hsu, H.-C. Huang | |
| Nonstationary Gaussian scale mixtures for spatial extremes | |
| E0523: S. Kim, C.Y. Lim, Y. Rho | |
| Spatio-temporal analysis of dependent risk with an application to cyberattacks data | |
| E0559: S. Tzeng, B.-Y. Chen, H.-C. Huang | |
| Contiguous segmentation of second-order non-stationary spatial processes | |
| E0538: H.-C. Huang, C.-S. Chen, Y.-H. Chiou | |
| Nonstationary spatial modeling, estimation, and prediction using a divide-and-conquer approach |
| Session EO312 | Room: 704 |
| Statistical design and modeling for life and climate sciences | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Andreas Futschik | Organizer: Andreas Futschik |
| E0590: W. Mueller, A. Pazman, M. Hainy | |
| A convex approach to optimum design of experiments with correlated observations | |
| E0564: H. Kishino, R. Nakamichi, S. Kitada | |
| Genetic adaptations in the population history of Arabidopsis thaliana | |
| E0546: A. Futschik | |
| A new approach for estimating the largest mean in a Gaussian mixture model with applications in population genetics | |
| E0749: Y. Wang | |
| Haplotype reconstruction via Bayesian linear models with unknown design | |
| E0612: B. Clarke, A. Pilkington, D. Diepeveen | |
| Robustifying an exact test for heteroscedasticity in a two-way layout in variety frost trials with a covariate |
| Session EO015 | Room: 705 |
| Recent advances in high-dimensional data analysis | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Kazuyoshi Yata | Organizer: Kazuyoshi Yata |
| E0786: K. Egashira, K. Yata, M. Aoshima | |
| Asymptotic behaviors of k-means under high dimensional settings | |
| E0588: T. Nakagawa, H. Watanabe, M. Hyodo | |
| Kick-one-out-based variable selection method for Euclidean distance-based classifier in high-dimensional settings | |
| E0814: Y. Umezu | |
| Sure screening for interaction effect in generalized linear models | |
| E0707: T. Nishiyama, M. Hyodo | |
| Linear hypothesis testing on mean vectors for factor model in high-dimensional settings | |
| E0462: Y. Akama | |
| Correlation matrix of factor model: Fluctuation of largest eigenvalue, scaling of bulk eigenvalues, and stock market |
| Session EO178 | Room: 709 |
| New topics in mathematical statistics | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Yoshihide Kakizawa | Organizer: Yoichi Nishiyama |
| E0507: K. Fujimori, K. Tsukuda | |
| The Dantzig selector for semiparametric models of stochastic processes | |
| E0569: K. Tsukuda, S. Matsuura | |
| A study on estimation in multivariate allometric regression | |
| E0709: K. Kawamoto, Y. Goto, K. Tsukuda | |
| Evaluating the error probability of the spectral clustering algorithm in the allometric extension model | |
| E0712: Y. Takagi | |
| Estimation of $n$ in the binomial $(n,p)$ distribution with both parameters unknown | |
| E0722: Y. Kakizawa | |
| Higher-order density derivative estimation for nonnegative data |
| Session EC324 | Room: 201 |
| Applied econometrics I | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Chong Dae Kim | Organizer: EcoSta |
| E1021: H. Han, P. Pan | |
| Exploring house price momentum in the US after the subprime mortgage crisis | |
| E1096: H. Chen, H. Nishino | |
| Bayesian multi-population Lee-Carter model applied to Japanese mortality data | |
| E1077: C.D. Kim | |
| An analysis of increased mortgage interest rates on the housing market in Germany using the BSTS Model | |
| E0265: A. Shrivastava, M. Sahoo, T. Sonna, J.M. Anthony | |
| Measuring contagion effects of crude oil prices on sectoral stock price indices in India | |
| E1248: C.-C. Chiu, L.-J. Kao, T.K. Liu | |
| Analyzing market response to SFCR in European insurance with topic modeling and deep learning methods |
| Session EC319 | Room: 203 |
| Mixed models | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Pavlo Mozharovskyi | Organizer: EcoSta |
| E0216: X. Ning, F. Hui, A. Welsh | |
| Asymptotic results for penalised quasi-likelihood estimation in generalised linear mixed models | |
| E0355: Z. Lyu | |
| Increasing sample size asymptotic for two-way crossed mixed effect model | |
| E1072: K. Momoki, T. Yoshida | |
| Mixed effects models for large sized clustered extremes | |
| E1090: E. Yanchenko | |
| The R2D2 prior for generalized linear mixed models | |
| E1098: A. Gutierrez Vargas, M. Vandebroek, M. Meulders | |
| MixTasteNet: A neural-embedded mixed logit model |
| Session EC317 | Room: 708 |
| Functional data analysis | Tuesday 01.8.2023 16:30 - 18:35 |
| Chair: Alexander Petersen | Organizer: EcoSta |
| E1239: X. Li | |
| Functional adaptive double-sparsity estimator for functional linear regression with multiple functional covariates | |
| E0459: J.M. Jeon, G. Van Bever | |
| Additive regression with general imperfect variables | |
| E0531: K. Yu, J. Taylor | |
| Riemannian functional regression and reproducing kernel tensor Hilbert spaces | |
| E0615: Y. Lim | |
| Functional principal component analysis for partially observed elliptical process | |
| E1159: R. Rocci, S.A. Gattone | |
| Simultaneous clustering and dimensionality reduction of functional data |
| Parallel session F: EcoSta2023 | Wednesday 02.8.2023 | 08:15 - 10:20 |
| Session EO252 | Room: 03 |
| Recent advances in statistical theory and methods | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Arlene Kyoung Hee Kim | Organizer: Arlene Kyoung Hee Kim |
| E0359: H. Lim, A.K.H. Kim | |
| Unpaired regression for a discrete response via Poisson quantiles matching | |
| E0767: Y. Kim, H. Chung | |
| A comprehensive framework for investigating multiple latent class variables | |
| E0522: H. Kim | |
| Variable selection for AUC-optimizing classification in diverging dimensions | |
| E0334: K.-Y. Bak, J.Y. Koo | |
| Nonparametric reduced-rank estimation of multiple regression functions | |
| E0696: T. Choi, S. Park, H. Cho, S. Choi | |
| Interval-censored linear quantile regression |
| Session EO008 | Room: 04 |
| Recent advances in causal inferences | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Zheng Zhang | Organizer: Wei Huang |
| E0172: Y. Zhang | |
| A conditional linear combination test with many weak instruments | |
| E0224: L. Wang, D. Tang, D. Kong, L. Wang | |
| The synthetic instrument | |
| E1273: Z. Guo | |
| Causal inference with invalid instruments: Exploring nonlinear treatment models with machine learning | |
| E1293: W. Huang, Z. Zhang, H. Hou, C. Ai | |
| Nonparametric Uniform Inference for General Heterogeneous Treatment Effect Models and Measurement Errors |
| Session EO139 | Room: Virtual R01 |
| Recent advances in the analysis of data with complex structures | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Yuhang Xu | Organizer: Xin Wang, Yuhang Xu |
| E0239: J. Mu, L. Jin | |
| On spatial generalized autoregressive conditional heteroskedasticity varying coefficient models | |
| E0241: Y. Xu, T. Vu, Y. Qiu | |
| Shifting-corrected regularized regression for 1H NMR metabolomics identification and quantification | |
| E0242: X. Wang, X. Zhang, Z. Zhu | |
| Clustered coefficient regression models for Poisson process with an application to seasonal warranty claim data | |
| E0387: J. Zhang, J. Bailer, A. Helling | |
| Comparing methods for determining power priors based on different congruence measures | |
| E0420: S. Kim, S.K. Lee, M.-O. Kim, H. Hong | |
| Longitudinal disparity decomposition under the varying-coefficient framework |
| Session EO090 | Room: Virtual R02 |
| Estimation of eigenvectors and covariance matrices in high dimensions | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Lisa Goldberg | Organizer: Lisa Goldberg |
| E0304: S. Jung | |
| James-Stein Estimator of moderately-spiked leading eigenvector | |
| E0758: S. Begusic | |
| Issues in large covariance matrix estimation for portfolio risk prediction | |
| E1227: L. Goldberg, A. Kercheval, H. Gurdogan | |
| James-Stein for eigenvectors with applications to constrained optimization | |
| E1232: Y. Lee | |
| Optimal regularization of the first principal component | |
| E1257: A. Shkolnik | |
| Beyond James-Stein estimation for PCA |
| Session EO052 | Room: 102 |
| Recent developments in estimation methods: Theory and applications | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Zhihua Su | Organizer: Zhihua Su |
| E1011: D. Eck | |
| Comparing baseball players across eras via the novel full house model | |
| E1015: B. Karmakar, G. Mukherjee, W. Kar | |
| Penalized synthetic control method for truncated data with latent clustering | |
| E1031: W. Qian, S. Ding | |
| Nonconvex-regularized integrative sufficient dimension reduction for multi-source data | |
| E1044: A. Linero, A. Ting | |
| Estimating heterogeneous causal mediation effects with bayesian decision tree ensembles | |
| E1286: Z. Su, K. Khare | |
| Response variable selection in multivariate linear regression |
| Session EO050 | Room: 201 |
| Weighting and dynamic approaches to causal inference | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Luke Keele | Organizer: Luke Keele |
| E0270: J. Zubizarreta, A. Chattopadhyay, C. Morris | |
| Balanced and robust randomized treatment assignments: The finite selection model | |
| E0274: L. Keele | |
| Approximate balancing weights for clustered observational study designs | |
| E0593: J. Roy, A. Oganisian | |
| Bayesian nonparametric methods for longitudinal mediation with informative continuous-time treatment decisions | |
| E0599: A. Oganisian, J. Roy | |
| Bayesian semiparametric models for informatively timed, dynamic treatments with incomplete covariate trajectories | |
| E0894: A. Spieker | |
| Longitudinal causal analysis of HIV antiretroviral therapy effects on weight gain |
| Session EO169 | Room: 203 |
| Causal machine learning with high dimensional modeling | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Tiffany Tang | Organizer: Zhe Fei |
| E0682: K. Kato, Z. Goldfeld, R. Sadhu | |
| Limit theorems for semidiscrete optimal transport maps | |
| E0498: L. Gao, Y. Fan, J. Lv, E. Demirkaya, P. Vossler, J. Wang | |
| Optimal nonparametric inference with two-scale distributional nearest neighbors | |
| E0566: Z. He | |
| GhostKnockoff inference empowers identification of putative causal variants in genome-wide association studies | |
| E0604: T. Tang, A. Agarwal, A. Kenney, Y.S. Tan, B. Yu | |
| MDI+: A flexible feature importance framework for random forests | |
| E0514: Z. Fei | |
| Prediction intervals with high dimensional models: With applications in LASSO and deep neural networks |
| Session EO227 | Room: 503 |
| Advances in Bayesian theory and computing | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Antonio Lijoi | Organizer: Antonio Lijoi |
| E0414: B. Franzolini, M. De Iorio | |
| Conditional partial exchangeability: A probabilistic framework for multi-view clustering | |
| E0486: F. Camerlenghi, A. Colombi, R. Argiento, L. Paci | |
| Dependent nonparametric priors based on finite point processes | |
| E0797: I. Ohn | |
| Adaptive variational Bayes | |
| E0865: S. Mano | |
| Modeling exchangeable sequences by mixture of mixture and its application | |
| E0870: S. Sugasawa, T. Wakayama, G. Kobayashi | |
| Bayesian spatio-temporal clustering of functional data |
| Session EO193 | Room: 506 |
| Recent advances at the intersection of statistics and machine learning | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Yichen Cheng | Organizer: Yichen Cheng |
| E0310: S.L.L. Tan | |
| Analytic natural gradient updates for Cholesky factor in Gaussian variational approximation | |
| E0407: M. Chen | |
| Predictive modeling of transcription-wide association studies via statistical learning methods | |
| E0354: N.M. Nguyen, M.-N. Tran, D. Nott, C. Drovandi | |
| Wasserstein Gaussianization and efficient variational Bayes for robust Bayesian synthetic likelihood | |
| E0678: Y. Cheng | |
| A Bayesian semi-supervised approach to keyphrase extraction | |
| E1048: P. Tseng, M.-N. Tran | |
| Convergence results of numerically estimated JKO scheme |
| Session EO128 | Room: 603 |
| Applied mathematics, statistics, and AI in portfolio optimization | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Chi Seng Pun | Organizer: Chi Seng Pun |
| E0508: D. Zhu, C.S. Pun | |
| The constrained Dantzig-type estimator: An application to selection of high-dimensional portfolios | |
| E0529: N.S. Lesmana, C.S. Pun | |
| Equilibrium Control Learning under Cumulative Prospect Theory: Quantile Regression Meets Reinforcement Learning | |
| E0624: K. Park, D. Bartl, A. Neufeld | |
| Sensitivity of robust optimization problems with ambiguity on semimartingale differential characteristics | |
| E0917: Y. Lee | |
| Portfolio selection based on anomaly detection using GANs | |
| E1270: J. Tang | |
| Understanding the difficulty of achieving dynamic optimality in time inconsistent problems |
| Session EO030 | Room: 604 |
| Recent advances in time series econometrics | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Kaiji Motegi | Organizer: Kaiji Motegi |
| E0490: X. Cai | |
| Time-varying ambiguity shocks and business cycles | |
| E0587: W. Zhang | |
| Can NFTs risk hedge other traditional assets after the COVID19 pandemic? | |
| E0547: S.Y. Hong | |
| Comparing factor models with conditioning information | |
| E0341: K. Maung | |
| Estimating high-dimensional Markov-switching VARs | |
| E0169: K. Motegi, J. Dennis | |
| Midastar: Threshold autoregression with data sampled at mixed frequencies |
| Session EO216 | Room: 605 |
| Stochastic frontier and productivity analysis with panel data applications | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Kai Sun | Organizer: Kai Sun |
| E0268: K. Sun, S. Kumbhakar | |
| A single-index smooth-coefficient stochastic frontier model | |
| E0544: T. Wang, K. Sun | |
| A semiparametric stochastic frontier model with two-way fixed effects and nonparametric inefficiency function | |
| E0926: K. Du, K. Sun | |
| Bank efficiency and credit risk: Evidence from the commercial banks in China | |
| E1116: F.K. Alemayehu, S. Kumbhakar, K. Sun | |
| Leveraging innovation for improved service productivity: Insights from endogenous stochastic frontier analysis | |
| E1188: Z. Hou | |
| Revisiting the public capital productivity puzzle | |
| E1332: J. Zhou | |
| Oil shock, policy uncertainty and stock return: An analysis based on the Bart method |
| Session EO149 | Room: 606 |
| Recent advances in time series and change-point analysis | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Chun Yip Yau | Organizer: Chun Yip Yau |
| E0426: Y. Li, C.T. Ng, C.Y. Yau | |
| GARCH-type factor model | |
| E0448: T.F. Ma, F. Wang, J. Zhu, A. Ives, K. Lewinska | |
| Scalable semiparametric spatio-temporal regression for large data analysis | |
| E0513: W.L. Ng | |
| Inference for multiple change-points in piecewise locally stationary time series | |
| E0586: S.H.I. Leung | |
| Weighted kernel estimators for forecasting under breaks | |
| E0699: G. Yuan | |
| Generalized multivariate threshold autoregressive models with linearly partitioned threshold space |
| Session EO177 | Room: 702 |
| Recent development in network data analysis | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Yichuan Zhao | Organizer: Chenlei Leng |
| E0388: Y. Ma, W. Lan, C. Leng, T. Li, H. Wang | |
| Supervised centrality via sparse spatial autoregression | |
| E0438: W. Wang | |
| Spectral analysis on networks with covariates | |
| E0451: D. Xia | |
| Higher-order accurate two-sample network inference and network hashing | |
| E0558: W. Lan | |
| Testing stochastic block models via the maximum sampling entry-wise deviation | |
| E0885: C.M. Le | |
| Variational inference: Posterior threshold improves network clustering accuracy in sparse regimes |
| Session EO107 | Room: 703 |
| Trustworthy and efficient machine learning | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Yao Li | Organizer: Yao Li |
| E0332: Y. Li, J. Lavond, M. Cheng | |
| Trusted aggregation (TAG): Model filtering backdoor defense in federated learning | |
| E0333: R. Lai | |
| Learning manifold-structured data using deep neural networks: Theory and applications | |
| E0343: J. Zheng, H. Huang, Y. Yi, Y. Li, S.-C. Lin | |
| Barycenter estimation of positive semi-definite matrices with Bures-Wasserstein distance | |
| E0620: P. Morala, R. Lillo, I. Ucar, J.A. Cifuentes | |
| Improving neural networks interpretability and trustworthiness using polynomials and feature interactions | |
| E0783: G. Chen | |
| Learning to make adherence-aware recommendations |
| Session EO198 | Room: 704 |
| Bayesian structure discovery | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Sameer Deshpande | Organizer: Sameer Deshpande |
| E0368: W. van den Boom, A. Beskos, M. De Iorio | |
| The G-Wishart weighted proposal algorithm: Efficient posterior computation for Gaussian graphical models | |
| E0936: S. Deshpande | |
| The multivariate spike-and-slab LASSO: Algorithms, asymptotics, and inference | |
| E0938: R. Bai | |
| Bayesian modal regression based on mixture distributions | |
| E0941: J. Datta, A. Bhadra, S. Banerjee, K. Sagar | |
| Structure learning with global-local prior-penalty dual | |
| E0943: M. Xu | |
| Identifying interpretable latent structures in factor analysis |
| Session EO109 | Room: 705 |
| Novel methods, algorithms and theory for high-dimensional data | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Qing Mai | Organizer: Qing Mai |
| E0174: J. Zeng, Q. Mai | |
| Robust estimation of central subspace under high-dimensional and elliptical-contoured design | |
| E0228: Y. Ke | |
| Learning high dimensional multi-response linear models with quantum optimization | |
| E0376: B. Wang, Q. Tang, Y. Gu | |
| fastkqr: A fast algorithm for kernel quantile regression | |
| E0392: N. Wang | |
| Statistical analysis for a penalized EM algorithm in high dimensional mixture linear regression model | |
| E0978: Q. Song | |
| Optimal false discovery control of minimax estimators |
| Session EO083 | Room: 708 |
| Novel statistical approaches to brain signals and images | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Hernando Ombao | Organizer: Hernando Ombao |
| E0967: D. Bolin | |
| Gaussian random fields on networks and metric graphs | |
| E0975: C.-M. Ting, J. Skipper, F. Noman, S. Small, H. Ombao | |
| Low-rank and sparse decomposition for brain functional connectivity in naturalistic fMRI data | |
| E1106: J. Kornak, K. Young, E. Friedman, K. Bakas, H. Ombao | |
| Bayesian image analysis in Fourier space for neuroimaging | |
| E1262: S. Jiao, R. Frostig, H. Ombao | |
| Filtrated common functional principal component analysis of multi-group functional data | |
| E0942: R. Krafty, H. Fu, L. Tang, O. Rosen, A. Hipwell, T. Huppert | |
| Covariate-guided mixture of multivariate time series experts for interpretable analysis of fNIRS data |
| Session EO228 | Room: 709 |
| Statistical ML in cybersecurity | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Lekha Patel | Organizer: Fletcher Christensen |
| E0229: F. Sanna Passino, A. Mantziou, D. Ghani, P. Thiede, R. Bevington, N. Heard | |
| Unsupervised attack pattern detection in honeypot data using Bayesian topic modelling | |
| E0595: M. Eren, J. Moore, E. Skau, E. Moore, M. Bhattarai, G. Chennupati, B. Alexandrov | |
| General-purpose unsupervised cyber anomaly detection via non-negative tensor factorization | |
| E0634: K. Shuler, A. Foss, C. Ting, T. Bauer, R. Field | |
| Statistical properties of compression analytics | |
| E0706: F. Christensen, E. Schwertner-Watson, L. Patel, G. Huerta, D. McGeehan | |
| Multi-attribute utility elicitation for real-time network anomaly detection | |
| E0888: T. McCormick, S. Wilkins-Reeves | |
| Local estimation and testing of latent network curvature |
| Session EC323 | Room: 02 |
| Data mining and education | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Brenda Betancourt | Organizer: EcoSta |
| Session EC320 | Room: 701 |
| Forecasting in applications | Wednesday 02.8.2023 08:15 - 10:20 |
| Chair: Rogemar Mamon | Organizer: EcoSta |
| E1213: R. Lacaza | |
| Forecasting Philippine economic growth using mixed frequency data: MIDAS versus MF-DLFM | |
| E0226: M. Costa, D. Magueta, S. Espadilha | |
| Modeling and forecasting of sales in fuel retail market: The factors that boost a fuel station's sales | |
| E0235: M. Monteiro, D. Neves, M.J. Felicio | |
| Forecasting tyre sales: Competitive models to improve inventory in a small business | |
| E0285: A.M. Goncalves, S. Lima, M. Costa | |
| Time series forecasting approaches to retail sales in EU Countries: Portugal and its major trading partners | |
| E0986: T. Supapakorn, S. Intarapak, W. Vuthipongse | |
| Forecasting of expenditures from foreign tourists traveling to Thailand |
| Parallel session G: EcoSta2023 | Wednesday 02.8.2023 | 10:50 - 12:30 |
| Session EV253 | Room: 701 |
| Time series and spatial statistics (virtual) | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Kun Chen | Organizer: EcoSta |
| E0282: D. Cheng | |
| Multiple testing of local extrema for detecting change points under nonstationary Gaussian noise | |
| E1197: P. Chen | |
| Vector error correction models with stationary and nonstationary variables | |
| E0324: R. Liu, X. Chen, Z. Shang | |
| Statistical inference with stochastic gradient methods under $\phi$-mixing data | |
| E1263: J.M. Loh, G. Luan | |
| Inference for spatial autoregressive models using stochastic gradient descent |
| Session EI002 | Room: 102 |
| Mathematical statistics and time series analysis | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Yan Liu | Organizer: Yan Liu |
| E0161: Y. Nishiyama | |
| A stochastic maximal inequality and its applications | |
| E0963: N.H. Chan | |
| Statistical Inference for Glaucoma Detection | |
| E1023: Y. Feng | |
| Learning from similar linear representations: Adaptivity, minimaxity, and robustness |
| Session EO124 | Room: 02 |
| New developments in microbiome research | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Julia Fukuyama | Organizer: Gen Li |
| E0249: E. Smirnova | |
| Quantifying major sources of technical variability in microbiome sequencing lab protocols | |
| E0439: T. Wang, R. Jiang, X. Zhan | |
| A flexible zero-inflated Poisson-Gamma model with application to microbiome sequence count data | |
| E0458: Y. Hu | |
| Testing microbiome associations with survival times | |
| E1137: L. Shenhav | |
| Context-aware dimensionality reduction of microbial ecosystem dynamics |
| Session EO019 | Room: 03 |
| New advances in statistical learning for image, process and clinical data | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Tiejun Tong | Organizer: Tiejun Tong |
| E0301: L. Chen, J. Liu | |
| Understanding differential item functioning using process data | |
| E0582: J. Wei, P. He, T. Tong | |
| Estimating the reciprocal of a binomial proportion | |
| E0937: Z. Li | |
| Introduction to differencing method and the application in testing no effect | |
| E1076: M. Liu, Y. Yang, Z. Shang | |
| Scalable statistical inference in non-parametric least squares |
| Session EO308 | Room: 04 |
| Optimal experimental designs: Recent advances and applications | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Saumen Mandal | Organizer: Saumen Mandal |
| E1079: L. Wang | |
| Complex innovative design pilot program and a potential proposal | |
| E0640: K. Hunter, K. Porter, L. Miratrix | |
| PUMP: Estimating power when adjusting for multiple outcomes in multi-level experiments | |
| E0812: S. Mandal, X. Zheng | |
| Optimal designs for matching adjusted indirect comparison | |
| E0823: S. Ghosh | |
| An algorithm for searching optimal variance component estimators in linear mixed models |
| Session EO028 | Room: Virtual R01 |
| New challenges for complex and large-scale data | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Yichuan Zhao | Organizer: Yichuan Zhao |
| Session EO140 | Room: Virtual R02 |
| Recent developments for modeling high-dimensional and complex data | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Wenbo Wu | Organizer: Wenbo Wu |
| E1281: R. Widjaja | |
| On partial envelop approach for modeling spatial-temporally dependent data | |
| E1287: W. Wu | |
| On sufficient variable screening using log odds ratio filter | |
| E1289: D. Li | |
| Reproducible learning for accelerated failure time models via deep knockoffs | |
| E1298: Y. Bao, H. Dai, W. Liang | |
| Distributed instrumental variable analysis in three UK studies |
| Session EO185 | Room: 201 |
| Recent advances in causal inference and missing data | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: BaoLuo Sun | Organizer: BaoLuo Sun |
| Session EO202 | Room: 203 |
| Statistical advances in genetic epidemiology | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Debashree Ray | Organizer: Debashree Ray |
| E0251: N. Zhao | |
| Integrative analysis of multiple microbiome studies | |
| E0372: D. Ray | |
| Meta-analysis in family-based study of disease subtypes | |
| E0446: I. Ionita-Laza | |
| Knockoff-based statistics for the identification of putative causal loci in genetic studies | |
| E0887: J. Witte | |
| Polygenic risk score methods to improve disease screening |
| Session EO164 | Room: 503 |
| Recent advances in design and analysis of complex experiments | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Luke Keele | Organizer: Xinwei Deng |
| E0326: M.-C. Chang | |
| Supervised stratified subsampling: An approach to big data predictive analytics | |
| E0720: C. Shi, H. Xu | |
| A projection space-filling criterion and related optimality results | |
| E1089: W. Zheng | |
| Thompson sampling with discrete support | |
| E1107: Y. Li | |
| A maximin $\Phi_{p}$-efficient design for multivariate generalized linear models |
| Session EO249 | Room: 506 |
| Statistics on manifolds | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Tomonari Sei | Organizer: Tomonari Sei |
| E0929: N. Deb | |
| Sinkhorn diffusion and Wasserstein mirror gradient flows | |
| E0727: T.L.J. Ng, A. Zammit Mangion | |
| Mixture of normalizing flows for spherical density estimation | |
| E0799: Y. Takazawa, T. Sei | |
| Theoretical properties of log-concave projections in CAT(0) orthant space | |
| E1034: K. Yano, T. Sei | |
| Minimum information dependence modeling for mixed-domain data analysis |
| Session EO014 | Room: 603 |
| Statistical analysis in crime, insurance and production | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Boris Choy | Organizer: Boris Choy |
| E0659: J. Wang | |
| The effect of parole supervision on recidivism in New South Wales, Australia | |
| E0671: T. Fung, J. Wang | |
| Modelling COVID and crime in the US as hierarchical time series | |
| E0690: S. Gao, B. Choy, J. Gao | |
| Loss reserving using geometric processes | |
| E1245: B. Choy | |
| Stochastic frontier analysis with scale mixtures of normal distributions |
| Session EO048 | Room: 604 |
| Recent developments on panel data analysis | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Wendun Wang | Organizer: Wendun Wang |
| E0400: X. Zhang, W. Wang, X. Zhang | |
| Asymptotic properties of the synthetic control method | |
| E0461: X. Leng | |
| Panel quantile regression for extreme risk | |
| E0721: Y. Sun, X. Leng | |
| Debiased inference for nonlinear panel maximum-likelihood models with two-way fixed effects | |
| E1012: K. Miao, L. Su, X. Lu | |
| Estimation of heterogeneous panel data models with an application to program evaluation |
| Session EO108 | Room: 605 |
| New advances in Gaussian process modeling and computer experiments | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Chih-Li Sung | Organizer: Chih-Li Sung |
| Session EO129 | Room: 606 |
| Econometric modeling with time series | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Tao Wang | Organizer: Tao Wang |
| E0237: S. Wang, Y. Tu | |
| Model averaging factor-augmented quantile regressions with smooth structural change | |
| E0391: T. Wang | |
| Kernel mode-based varying coefficient models with nonstationary regressors | |
| E1290: B. Antoine, O. Boldea, N. Zaccaria | |
| Inference in linear models with structural changes and mixed identification strength | |
| E1108: E. Kurozumi | |
| Fluctuation-type monitoring test for explosive behavior |
| Session EO098 | Room: 702 |
| Dynamic topological data analysis on time series data | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Moo K Chung | Organizer: Moo K Chung |
| E0475: M.K. Chung | |
| Topological state-space estimation of dynamically changing functional human brain networks | |
| E0557: H. Ombao, A. El Yaagoubi Bourakna, M.K. Chung, S. Jiao | |
| Spectral topological data analysis for EEG brain signals | |
| E0904: J.-H. Jung | |
| Topological data analysis of time-series data | |
| E1283: Y. Wang, J. Yin | |
| Topological clustering and inference on heat-diffusion estimates of persistence diagrams |
| Session EO103 | Room: 703 |
| Advances in network data analysis | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Guodong Li | Organizer: Philip Yu |
| E0541: G. Li | |
| An efficient tensor regression for high-dimensional data | |
| E0267: J. Gu, P. Yu | |
| Joint latent space models for ranking data and social network | |
| E0951: P. Yu, Y. Zhuang, C. Wang | |
| Preference matrix completion with multiple network views based on graph neural networks |
| Session EO088 | Room: 704 |
| Ecological statistics modeling | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Wen-Han Hwang | Organizer: Wen-Han Hwang |
| E0705: Y. Wang, I. Flint, P. Vesk, N. Golding, A. xia | |
| Saturated pairwise interaction Gibbs point process as a joint species distribution model | |
| E0841: M. Schofield | |
| Estimating population size: The importance of model and estimator choice | |
| E0853: W.-H. Hwang | |
| Nc-mixture occupancy models | |
| E1168: C. Ling | |
| Spatio-temporal joint modelling on moderate and extreme air pollution in Spain |
| Session EO065 | Room: 705 |
| Theory and methods for high-dimensional and complex data | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Anuradha Roy | Organizer: Anuradha Roy |
| E0390: T. Abe, M. Kuroda | |
| Simple EM algorithm for Cauchy-type distributions | |
| E0397: A. Ishii, K. Yata, M. Aoshima | |
| Quadratic classifiers for high-dimensional noisy data | |
| E0528: F. Maturo, A. Porreca | |
| Supervised classification of high-dimensional data through functional data augmentation and random forest | |
| E0575: T. Kim, I. Kim, K.-A. Lee | |
| Weighted conditional network testing for multiple high-dimensional correlated data sets |
| Session EO250 | Room: 708 |
| New statistical methods in neuroimaging | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: John Kornak | Organizer: John Kornak |
| E0476: J. Harezlak, L. Xiao | |
| Biclustering multivariate longitudinal data: Application to white matter recovery trajectories after sport-related mTBI | |
| E1115: D. Tudorascu | |
| Linear effect of inter-scanner variability: Insights from paired cross-scanner T1-weighted images in elderly subjects | |
| E1180: A. El Yaagoubi Bourakna, M.K. Chung, H. Ombao | |
| Causality-based topological ranking of brain regions during epileptic seizure | |
| E1264: A. Scheffler, R. Guhaniyogi, R. Gutierrez | |
| Bayesian multi-object data integration in the study of primary progressive aphasia |
| Session EO244 | Room: 709 |
| The art and science of predictive modeling: From theory to practice | Wednesday 02.8.2023 10:50 - 12:30 |
| Chair: Le Zhou | Organizer: Boxiang Wang |
| Parallel session H: EcoSta2023 | Wednesday 02.8.2023 | 14:00 - 15:40 |
| Session EV285 | Room: Virtual R01 |
| Applied econometrics and statistics | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Marica Manisera | Organizer: EcoSta |
| E1032: I. van de Werve, S.J. Koopman | |
| Finding the European crime drop using a panel data model with stochastic trends | |
| E1150: M. Bosupeng | |
| A time-varying causality approach for Botswana's trade balance and its determinants | |
| E1143: T.-H. Ke, H.-C. Huang, H.-Y. Shih | |
| Exploratory data analysis of innovation momentum: The application of semiconductor industry granted patents |
| Session EI004 | Room: 102 |
| Advances in Bayesian nonparametrics | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Michele Guindani | Organizer: Michele Guindani |
| E0156: I. Pruenster, B. Franzolini, A. Lijoi, G. Rebaudo | |
| Nonparametric priors for partially exchangeable data: dependence structure and borrowing of information | |
| E0157: J. Lee | |
| Post-processed posteriors for high-dimensional covariances | |
| E0158: L. Nguyen | |
| Inverse bounds and posterior contraction of the latent mixing measures |
| Session EO171 | Room: 02 |
| Joint modelling of multi-outcome data | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Christiana Charalambous | Organizer: Christiana Charalambous |
| E0280: R. Miao, C. Charalambous | |
| A general joint latent class model of longitudinal and survival data with covariance modelling | |
| E0717: T. Chekouo | |
| A two-level copula joint model for joint analysis of longitudinal and competing risks data | |
| E0983: C. Ma, J. Pan | |
| Modeling past event feedback through biomarker dynamics in the multistate event analysis for cardiovascular disease data | |
| E1130: C. Charalambous, R. Miao | |
| Joint models for multi-outcome data and covariance structures via a Bayesian approach |
| Session EO251 | Room: 03 |
| Advanced statistical methods for biomedical data | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Eunjee Lee | Organizer: Eunjee Lee |
| E0649: J.Y. Park | |
| A fast and powerful spatial-extent inference for testing variance components in reliability and heritability studies | |
| E0703: S. Kim, E. Lee | |
| A deep attention LSTM embedded aggregation network for multiple histopathological images | |
| E0779: M. Miranda, J. Morris | |
| A fully Bayesian tensor basis model for multi-subject task fMRI data | |
| E0796: L. Bantis, J. Tsimikas | |
| On optimal biomarker cutoffs accounting for misclassification costs in diagnostic trilemmas |
| Session EO307 | Room: 04 |
| Survival analysis and biomedical statistics | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Dongdong Li | Organizer: Takeshi Emura |
| Session EO091 | Room: Virtual R02 |
| Statistical methods and dependence in space and/or time | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Moritz Jirak | Organizer: Moritz Jirak |
| E1084: M. Lopes | |
| Dimension-free rates of bootstrap approximation for spectral statistics in high-dimensional PCA | |
| E1162: M. Wahl | |
| A kernel-based analysis of Laplacian eigenmaps | |
| E1265: J. Brutsche, A. Rohde | |
| Sharp adaptive similarity testing with pathwise stability for ergodic diffusions | |
| E1278: M. Jirak | |
| Weak dependence and optimal quantitative self-normalized central limit theorems |
| Session EO150 | Room: 201 |
| Causal inference in observational studies | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Yeonseung Chung | Organizer: Yeonseung Chung |
| E1029: C. Kim | |
| Bayesian additive regression trees model for high-dimensional potential confounders | |
| E1117: S. Bong, K. Lee, F. Dominici | |
| Differential recall bias in self-reported risk factors in observational studies | |
| E1198: K. Kim, E. Kennedy, L. Wasserman | |
| Causal clustering | |
| E1308: W. LEE | |
| Causal inference in environmental epidemiology research with large-size retrospective cohort data |
| Session EO145 | Room: 203 |
| Recent advances on quantile and tail analysis | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Qian Xiao | Organizer: Ting Zhang |
| E0230: Y. Zhao | |
| Whittle estimation based on the extremal spectral density of a heavy-tailed random field | |
| E0803: W. Wu, S.S. Dhar | |
| Comparing time varying regression quantiles under shift invariance | |
| E0993: Y. Hou | |
| Panel quantile regression for extreme risk | |
| E1003: D. Li | |
| Systemic and systematic risks driven marginal expected shortfall |
| Session EO223 | Room: 503 |
| Bayesian modelling with mixture models | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Cheng Li | Organizer: Tommaso Rigon |
| E0618: F. Barile, B. Nipoti, S. Lunagomez | |
| Flexible modelling of heterogeneous populations of networks: A Bayesian nonparametric approach | |
| E0860: C. Del Sole, A. Lijoi, I. Pruenster | |
| Hierarchically dependent mixture hazard rates for modelling competing risks | |
| E0882: A. Zito, T. Rigon, D. Dunson | |
| Bayesian nonparametric modelling of latent partitions via Stirling-gamma priors | |
| E0886: C.-L. Hsu, T. Rigon, D. Dunson | |
| Joint species distribution modeling with mixture models |
| Session EO046 | Room: 506 |
| Statistical learning in finance | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Li-Hsien Sun | Organizer: Li-Hsien Sun |
| E0734: C.-L. Kao, T. Pang, C.-D. Fuh | |
| Kullback-Leibler divergence and Akaike information criterion in general hidden Markov models | |
| E1042: L.-H. Sun, M.-H. Hsieh, D.-H. Kuo | |
| Change point detection through copula-based Markov models | |
| E1095: C. Chao, M.-E. Wu, M.-H. Hsieh | |
| A Method for Quantify the Characteristics of Voltaties on Financial Assets by using Fuzzy | |
| E1059: C. Chang, T. Emura, S.-F. Huang | |
| Estimation of threshold boundary regression models |
| Session EO055 | Room: 604 |
| Econometrics and statistics for the digital asset economy | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Jeffrey Chu | Organizer: Stephen Chan, Jeffrey Chu |
| Session EO134 | Room: 606 |
| Recent developments in time-series and econometrics | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Shih-Feng Huang | Organizer: Shih-Feng Huang |
| E0316: J. Yang | |
| An asymptotic behaviour of a finite-section of the optimal causal filter | |
| E0488: L.-C. Lin, S.-W. Charng | |
| LIMOS--LightGBM interval Merton one-period-portfolio selection | |
| E0521: H.-C. Wong, C.-K. Ing, W.-J. Tsay | |
| Consistent autoregressive spectral estimates under GARCH-type noises | |
| E0167: S.-F. Huang | |
| Hysteretic multivariate Bayesian structural GARCH model with soft information |
| Session EO119 | Room: 703 |
| New directions in time series analysis | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Sumanta Basu | Organizer: Sumanta Basu |
| E0817: S. Lahiry, S. Basu, D. Mukherjee, K. Karpman | |
| Exploring financial networks using quantile regression and Granger causality | |
| E0878: M. Bhattacharjee | |
| Asymptotic of large autocovariance matrices | |
| E0753: S. Deb | |
| Using t-SNE in analyzing multivariate time series data | |
| E0898: M. Duker | |
| High-dimensional latent Gaussian count time series | |
| E0830: A. Betken, H. Dehling, A. Schnurr, I. Nuessgen, J. Woerner, J. Buchsteiner, A. Betken | |
| Ordinal pattern based time series analysis |
| Session EO136 | Room: 705 |
| Recent advances of high-dimensional data analysis | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Jin-Ting Zhang | Organizer: Jin-Ting Zhang |
| E0201: T. Zhu, J.-T. Zhang | |
| A further study on Chen-Qin's test for two-sample Behrens-Fisher problems for high-dimensional data | |
| E0243: J.-T. Zhang, J.-T. Zhang, T. Zhu | |
| A fast and accurate kernel-based independence test | |
| E0273: D. Huang, F. Wang, D. Rubin, S. Kou | |
| Catalytic priors: Using synthetic data to specify prior distributions in Bayesian analysis | |
| E0676: T. Yu, P. Li, B. Chen, J. Qin | |
| Maximum profile binomial likelihood estimation for the semiparametric Box--Cox power transformation model |
| Session EO179 | Room: 708 |
| Snapshot on current functional data methodologies | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Frederic Ferraty | Organizer: Frederic Ferraty |
| E0499: D. Telesca | |
| Covariate adjusted mixed membership models for functional data | |
| E0580: F. Scheipl, M. Hermann | |
| Geometric and topological perspectives on unsupervised functional data analysis | |
| E0724: J. Song | |
| Functional predictor selection and its nonasymptotic behavior |
| Session EO151 | Room: 709 |
| Recent advances in panel data econometrics | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Takahide Yanagi | Organizer: Takahide Yanagi |
| E0217: Y. Wang | |
| Low-rank panel quantile regression: Estimation and inference | |
| E0179: S. Ishimaru | |
| What do we get from two-way fixed effects regressions? Implications from numerical equivalence | |
| E0478: A.A. Pua, M. Fritsch, J. Schnurbus | |
| Using extreme bounds analysis to assess reproducibility | |
| E0196: Y.L. Cheung | |
| Fixed-T estimation of matrix-valued factor models |
| Session EC303 | Room: 603 |
| Empirical finance | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Feiyu Jiang | Organizer: EcoSta |
| E1122: C.F.C. Chu, P.K.D. Chan | |
| Simulation of high-fidelity limit order book data with machine learning model for Asia exchange markets | |
| E1207: M. Jennings, C. Zhang, A. Cartea, M. Cucuringu | |
| A similarity-based approach to covariance forecasting |
| Session EC300 | Room: 605 |
| Macroeconometrics | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Caleb Miles | Organizer: EcoSta |
| E0444: J. Ma, Y. Han | |
| Estimating the interest rate trend in a shadow rate term structure model | |
| E0654: S. Streicher, A. Rathke | |
| Improving output gap estimation: A bottom-up approach | |
| E0852: B.D.T. Nguyen, T.T.H. Nguyen | |
| Macroprudential stress testing: A proposal for the United States fund sector | |
| E1176: L. Donayre, I. Panovska | |
| The speed of state-level recoveries |
| Session EC289 | Room: 701 |
| Applied statistics | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Wendun Wang | Organizer: EcoSta |
| E0307: S. Lee, J. Lim | |
| Censored experiments for computing the average run length | |
| E0810: T.-Y. Lin | |
| Comparing product quality using a distribution-wise index | |
| E1018: B. Yin, K. Hayakawa | |
| The mean group estimators for multi-level autoregressive models with intensive longitudinal data | |
| E1132: U. Dang, W. Tu, S. Dang | |
| Gaussian mixture models for changepoint detection |
| Session EC271 | Room: 702 |
| Networks and graphical models | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: Boris Choy | Organizer: EcoSta |
| E1001: P.H. Cheng | |
| Assessing weather risk: A non-parametric test for network independence with distance covariance | |
| E1163: T.K.H. Nguyen, D. Risso, M. Chiogna, K. Van Den Berge | |
| Structure learning of graphical models for count data, with applications to single-cell RNA sequencing | |
| E1313: K. Fu, J. Hu | |
| Two-sample test for stochastic block models via maximum entry-wise deviation | |
| E1214: T. Yang, J. Suzuki | |
| Extension of LiNGAM to functional data |
| Session EC260 | Room: 704 |
| Computational statistics and econometrics | Wednesday 02.8.2023 14:00 - 15:40 |
| Chair: David Nott | Organizer: EcoSta |
| E0728: D. Li | |
| A minibatch Gibbs sampler for scalable large-scale Bayesian inference on latent variable models | |
| E1120: J. Hou-Liu, R. Browne | |
| Generalized linear models for massive data via doubly-sketching | |
| E1182: A. Sharp, R. Browne | |
| Maximum contribution to the likelihood: An estimation approach for stochastic expectation-maximization algorithm | |
| E1282: C. Meng | |
| Efficient algorithms for large-scale optimal transport problems |
| Parallel session I: EcoSta2023 | Wednesday 02.8.2023 | 16:10 - 17:50 |
| Session EO200 | Room: 02 |
| Advances in time series econometrics | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Jihyun Kim | Organizer: Jihyun Kim |
| E0207: Y.-K. Kim, J. Kim | |
| Instrumental factor models for high-dimensional functional data | |
| E0212: S. Lee | |
| A trajectories-based approach to measuring intergenerational mobility | |
| E0213: W.-K. Seo, M. Nielsen, D. Seong | |
| Inference on nonstationarity and common stochastic trends in high-dimensional or functional time series | |
| E0219: B. Kwak, A. Kriwoluzky, O. Holtemoeller | |
| Is there an information channel of monetary policy? |
| Session EO099 | Room: 03 |
| High dimensional regression in biomedical applications | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Johan Lim | Organizer: Johan Lim |
| E0287: X. Wang, Y. Cheng, Y. Xia | |
| Bayesian multi-task learning for medicine recommendation based on online patient reviews | |
| E0533: S. Katayama | |
| High dimensional tests on multivariate regressions under confounding | |
| E0935: S. Park, J. Lim, X. Wang, T. Wang | |
| Selection problems in multiple instance learning | |
| E0996: O. Ozturk, O. Kravchuk, R. Jarrett | |
| Models for cluster randomised designs using ranked set sampling |
| Session EO025 | Room: 04 |
| Survival analysis with medical and health data science | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Takeshi Emura | Organizer: Takeshi Emura |
| E0244: Z. Zhang | |
| A bivariate time-varying copula joint model for longitudinal measurements and time-to-event data | |
| E0515: H.-W. Lin | |
| Statistical methods for integrating longitudinal and cross sectional data: A real case study | |
| E0844: N. Taketomi, K. Yamamoto, C. Chesneau, T. Emura | |
| Parametric distributions for survival analysis, a review and historical sketch | |
| E0940: D. Li | |
| Distributed Cox proportional hazards regression using summary-level information |
| Session EO135 | Room: Virtual R01 |
| Bayesian non-parametric modelling with applications | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Andrea Cremaschi | Organizer: Andrea Cremaschi |
| E0335: X. Miscouridou | |
| Cox-Hawkes: Doubly stochastic spatiotemporal Poisson processes | |
| E1030: R. Argiento, L. Paci, E. Filippi-Mazzola | |
| Model-based clustering for categorical data via Hamming distance | |
| E0502: M. De Iorio, W. van den Boom, A. Beskos | |
| Bayesian learning of graph substructures | |
| E0925: G. Page, J.J. Quinlan Binelli, M. Castro | |
| Joint random partition models for multivariate change point analysis |
| Session EO100 | Room: Virtual R02 |
| Machine learning theory and robustness | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Yiming Ying | Organizer: Yiming Ying, Andreas Christmann |
| E1039: Z.-C. Guo, X. Guo, L. Shi | |
| Convergence analysis for functional online learning algorithms | |
| E1110: H. Koehler | |
| Lp-consistency of regularized kernel methods and its connection to risk consistency | |
| E1179: D. Xiang | |
| Mathematical foundations of outcome weighted learning in precision medicine | |
| E1280: Y. Ying | |
| Generalization analysis for contrastive deep representation learning |
| Session EO201 | Room: 201 |
| Treatment effect heterogeneity and related topics | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Seojeong Jay Lee | Organizer: Seojeong Jay Lee |
| E0329: F. Yu | |
| Tests for heterogeneous treatment effect | |
| E0339: D. Kim, P. Pal | |
| Nonparametric estimation of sponsored search auctions and impacts of ad quality on search revenue | |
| E0716: S.J. Lee, V. Panchenko, W. Tian | |
| Synthetic controls with multiple outcomes: estimating the effects of NPIs in the COVID-19 Pandemic | |
| E0764: J. Choi | |
| How does a better design improve the OLS regression? |
| Session EO222 | Room: 203 |
| Advances in graphical models | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Federico Camerlenghi | Organizer: David Rossell |
| E0527: D. Sulem, V. Rivoirard, J. Rousseau | |
| Scalable variational Bayes methods for interacting point processes | |
| E0660: A. Avalos Pacheco, A. Lazzerini, M. Lupparelli, F. Stingo | |
| Bayesian inference of multiple Ising models for heterogeneous data | |
| E0732: M. Lupparelli, L. La Rocca, A. Roverato | |
| An ANOVA-like decomposition of logistic regression parameters | |
| E1043: G. Consonni, F. Castelletti, M. Della Vedova | |
| Causal inference for categorical graphical models |
| Session EO143 | Room: 503 |
| Recent advances in Bayesian methods: Prediction and causal inference | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Kenichiro McAlinn | Organizer: Kenichiro McAlinn |
| E1234: V. Pena | |
| Comparing two multivariate stochastic volatility models | |
| E1260: K. Takanashi, K. McAlinn | |
| Inadmissibility and transience | |
| E1274: M. Kato, A. Fukuda, K. Takanashi, K. McAlinn, A. Ohda, M. Imaizumi | |
| Synthetic control methods through predictive synthesis | |
| E1276: K. McAlinn, K. Takanashi, S. Sugasawa | |
| Bayesian causal synthesis for meta-inference on heterogeneous treatment effects |
| Session EO313 | Room: 603 |
| Financial modelling in changing market conditions | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Christina Erlwein-Sayer | Organizer: Christina Erlwein-Sayer |
| E0735: F. Woebbeking, N. Packham | |
| Correlation scenarios and correlation stress testing | |
| E0807: C. Erlwein-Sayer, S. Grimm, T. Sayer | |
| HMM-enhanced LSTM for electricity spot price prediction | |
| E0842: N. Packham | |
| Risk factor detection with methods from explainable ML | |
| E0417: A. Petukhina | |
| Blockchain characteristics and systematic risk: A neural network based factor model for cryptocurrencies |
| Session EO082 | Room: 604 |
| New advances in time series econometrics: Theory and applications | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Kun Chen | Organizer: Kun Chen |
| E0363: H.-H. Huang, S.-H. Yu, C.-K. Ing | |
| Negative moment bounds for autocovariance matrices of stationary processes driven by conditional heteroscedastic errors | |
| E1118: Y. Tao | |
| Does digital finance upgrade trickle-down consumption effect in China? | |
| E1091: R. Huang | |
| Sparse causal dynamic linear regression | |
| E1075: K. Chen, N.H. Chan, C.-K. Ing, H.-H. Huang | |
| Consistent order selection for ARFIMA processes |
| Session EO246 | Room: 605 |
| Estimation, inference and forecasting in panel data analysis | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Xiaoyi Han | Organizer: Xiaoyi Han |
| E0700: C. Yahui, H. Xiaoyi, Z. Jiajun | |
| GMM and root estimations of spatial dynamic panel data models with unknown heteroskedasticity and dominant units | |
| E0713: N. Liu | |
| Uniform inference for nonparametric panel model with fixed effects | |
| E0784: C.S.H. Wang | |
| Return and volatility forecasting in mixed panels | |
| E0981: X. Han, Y. Xu, Y. Huang, L. Fan, M. Xu, S. Gao | |
| Seeding efficient large-scale public health interventions in diverse spatial-social networks |
| Session EO199 | Room: 606 |
| Complex time series | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Feiyu Jiang | Organizer: Wai-keung Li |
| E0366: K. Lu, H. Yuan, Y. Guo, G. Li | |
| HAR-Ito models and their high-dimensional statistical inference | |
| E0449: K. Wei, Y. Xia | |
| Test of serial dependence or cross dependence for time series with underreporting | |
| E0483: K. Zhu | |
| Quantiled conditional variance, skewness, and kurtosis by Cornish-Fisher expansion | |
| E1172: W.-K. Li | |
| Testing for innovation symmetry in multivariate generalized autoregressive conditional heteroskedastic models |
| Session EO237 | Room: 701 |
| Statistics in sports | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Marica Manisera | Organizer: Paola Zuccolotto, Marica Manisera |
| E0622: C. Ekstrom, A.K. Jensen | |
| Having a ball: Evaluating scoring streaks and game excitement using in-match trend estimation | |
| E0530: A. Macis, M. Sandri, M. Manisera, P. Zuccolotto | |
| Evaluating the risk of injury in NBA players | |
| E0353: C. Ley, F. Felice, A. Groll | |
| Statistically enhanced learning for better predictions | |
| E0664: U. Brefeld | |
| Pattern recognition in elite soccer with only a few labeled situations |
| Session EO306 | Room: 702 |
| Recent developments in spectral image data analysis | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Yunlong Feng | Organizer: Yunlong Feng |
| Session EO067 | Room: 703 |
| Spatial and network econometrics | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Tadao Hoshino | Organizer: Tadao Hoshino |
| E0584: C.-S. Hsieh | |
| Unequally sampled networks: Biases and corrections | |
| E0686: D. Murakami, S. Sugasawa | |
| Sub-model aggregation for scalable spatially varying coefficient modeling | |
| E0864: Z. Yang, X. Meng | |
| Spatial panel data models with time-varying network structures and multi-dimensional fixed effects | |
| E0394: T. Hoshino | |
| Causal inference and interpretation of linear social interaction models with endogenous networks |
| Session EO068 | Room: 705 |
| Recent advances in large-scale data analysis | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Xiaojun Mao | Organizer: Xiaojun Mao |
| E0382: X. Wang | |
| Composite smoothed quantile regression | |
| E1310: X. Zhang | |
| Robust personalized federated learning with sparse penalization | |
| E1318: Y. Zhang | |
| An efficient tensor regression for high-dimensional data | |
| E1319: Z. Wang, X. Mao, J.K. Kim | |
| Functional calibration under non-probability survey sampling |
| Session EO023 | Room: 708 |
| High-dimensional and spatial functional data | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Alexander Petersen | Organizer: Alexander Petersen |
| E0269: E. Solea | |
| Joint estimation of heterogeneous non-Gaussian functional graphical models with fully and partially observed curves | |
| E0336: A. Datta | |
| Graphical Gaussian processes for high-dimensional multivariate spatial data | |
| E0958: H.L. Shang, Y. Sun, C.F. Jimenez Varon | |
| Forecasting high-dimensional functional time series: Application to sub-national age-specific mortality | |
| E0971: L. Shao, F. Yao | |
| Robust functional data analysis for discretely observed data |
| Session EO120 | Room: 709 |
| Advances in time series, random forests and causal inference | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Hiroshi Shiraishi | Organizer: Hiroshi Shiraishi |
| E0170: X. Zeng, Y. Kakizawa | |
| ADCINAR(1) process and bias-correction of some estimators | |
| E0460: H. Shiraishi, T. Nakamura, R. Suzuki | |
| Asymptotic property for generalized random forests | |
| E0525: T. Nakamura | |
| Variable importance measure for generalized random forest | |
| E0573: C. Benard | |
| Variable importance for random forests: Inconsistency and practical solutions for MDA and Shapley effects |
| Session EC256 | Room: 102 |
| Financial econometrics I | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Toshiaki Watanabe | Organizer: EcoSta |
| E0194: P. Fiszeder, M. Malecka | |
| Robust estimation of the range-based GARCH model: Application for cryptocurrencies | |
| E0509: A. Quaini, F. Trojani, M. Yuan | |
| Intrinsic factor risk premia | |
| E1244: M. Magris, A. Iosifidis | |
| Modelling volatility with variational inference priciples | |
| E0197: G. Mitrodima, J. Oberoi | |
| CAViaR models for value at risk and expected shortfall with long range dependency features |
| Session EC262 | Room: 506 |
| Bayesian methods | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Boris Choy | Organizer: EcoSta |
| E0992: G. Li, R. Leon-Gonzalez | |
| Nuisance parameters, modified profile likelihood and Jacobian prior | |
| E1222: S. Nakakita | |
| Langevin-type Monte Carlo algorithms for weakly differentiable non-convex potentials | |
| E1228: H. Park | |
| Bayesian estimation of covariate assisted principal regression for brain functional connectivity | |
| E1247: E. Mise, S. Dhami, A. al-Nowaihi, J. Cannam | |
| An efficient Bayesian estimation of nonlinear hierarchical decision models |
| Session EC275 | Room: 704 |
| Forecasting | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Kaiji Motegi | Organizer: EcoSta |
| E0205: P.J. Cayton | |
| Alternative percentage error measures for forecasting intermittent and lumpy time series | |
| E0415: V. Monschang, M. Trede, W. Bernd | |
| An improved test for uniform superior predictive ability | |
| E0964: C. Schult, K. Heinisch, F. Scaramello | |
| Advancing forecast accuracy analysis: A partial linear instrumental variable and double machine learning approach | |
| E1181: P. Piboonrungroj | |
| Comparison between forecasting and nowcasting of digital economy |
| Session EP326 | Room: Poster session I |
| Poster Session I | Wednesday 02.8.2023 16:10 - 17:50 |
| Chair: Cristian Gatu | Organizer: EcoSta |
| E0320: S.K. Choy, Y.L. Mo | |
| Unsupervised fuzzy statistical learning and its applications in image segmentation | |
| E0325: C.C. Siu, W.Y. Tsui, G. Ma | |
| Optimal investment with return predictability and trading frictions: An asymptotic approach | |
| E0330: C.K.W. Yu, J. Leung | |
| Subgradient methods for quasi-convex optimization with applications | |
| E0406: H.M. Ng, K.Y. Wong | |
| A global kernel estimator for partially linear varying coefficient additive hazards models | |
| E0572: K.L. Chu | |
| Bit-plane probability model and its application in image segmentation | |
| E0617: H. Kim, E. Lee | |
| Prediction of apartment sale price indices using functional linear models | |
| E0747: Y.S. Lee, E. Lee | |
| Detection of genetic variation related to Alzheimer's disease using functional data analysis | |
| E0848: N. Smit, R. de Jongh, H. Venter | |
| Good subsets approach to variable selection |
| Parallel session J: EcoSta2023 | Wednesday 02.8.2023 | 18:00 - 19:15 |
| Session EV263 | Room: 102 |
| Bayesian methods (virtual) | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Cheng Li | Organizer: EcoSta |
| E1068: C. Scricciolo, J. Rousseau | |
| Wasserstein convergence in Bayesian deconvolution models | |
| E1226: D. Gunawan, R. Kohn, P. Chatterjee | |
| The block-correlated pseudo marginal sampler for state space models | |
| E0927: C. Frevent, M.S. Ahmed, S. Dabo, M. Genin | |
| A Bayesian shared-frailty spatial scan statistic model for time-to-event data |
| Session EV278 | Room: 203 |
| Machine learning (virtual) | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Yongdai Kim | Organizer: EcoSta |
| E0491: Y. Zhang | |
| Learning rates of convolutional neural networks with correntropy induced loss | |
| E1093: S. Muehlbauer, E. Weber | |
| Machine learning for labor market matching | |
| E1133: S. Maggio, V. Distefano, S. De Iaco | |
| A hybrid two-step approach for assessing the probability of training needs on artificial intelligence systems |
| Session EO173 | Room: 04 |
| Survival analysis: Theory and methods | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Takeshi Emura | Organizer: Takeshi Emura |
| E0636: K. Burke, F.-Z. Jaouimaa, I.D. Ha | |
| Hierarchical penalized distributional regression models for survival data | |
| E0681: S. Schneider | |
| An approach for long-term survival data with dependent censoring | |
| E0846: C. Moreira | |
| Analysis of doubly truncated data |
| Session EO027 | Room: Virtual R01 |
| Asset pricing, and risk attitudes towards rare disasters | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Go Charles-Cadogan | Organizer: Go Charles-Cadogan |
| E1256: M. Zanecki | |
| On the predictability of stock returns using predictive equity analytics with dynamic state space | |
| E1320: J. Liang, C.Y.-H. Chen, B. Chen | |
| Robo-advising under rare disasters | |
| E1255: G. Charles-Cadogan | |
| Quantitative easing of fear during rare disasters |
| Session EO144 | Room: Virtual R02 |
| Environmental data modeling, prediction and risk assessment | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Stefano Rizzelli | Organizer: Stefano Rizzelli |
| E0856: S. Padoan, S. Rizzelli, C. Dombry | |
| Bayesian inference and probabilistic forecasting for the peaks over threshold approach | |
| E0837: J. Koh | |
| Predicting risks of temperature extremes using large-scale circulation patterns with r-Pareto processes | |
| E0579: M. Pegoraro | |
| Wasserstein distributional data analysis with application to wind forecasting | |
| E0585: M. Peruzzi | |
| Bayesian multi-species N-mixture models for large scale spatial data in community ecology |
| Session EO035 | Room: 201 |
| Advances in modelling ordinal and mixed-type data (virtual) | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Monia Ranalli | Organizer: Cristina Mollica |
| E0765: M. Angelelli, S. Arima, C. Catalano, E. Ciavolino | |
| Estimation and accuracy evaluation of cyber-risk prioritization for threat intelligence | |
| E1037: F. Porro | |
| An analysis of mine-related insurance data using a compositional approach | |
| E1124: M. Ranalli, R. Rocci | |
| Parsimonious and semi-constrained models for clustering mixed-type data through a composite likelihood approach |
| Session EO021 | Room: 506 |
| ML in electricity pricing, actuarial loss reserving and efficiency analysis | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Yuning Zhang | Organizer: Boris Choy |
| E1041: G. Kapoor, N. Wichitaksorn | |
| New Zealand electricity price forecasting: An analysis of statistical and machine learning models with feature selection | |
| E0648: Y. Zhang, B. Choy, J. Gao | |
| Stochastic loss reserving with long short term memory | |
| E1033: Z. Wei, H. Sang, N. Coulibaly | |
| Bayesian nonparametric machine learning approach for efficiency analysis |
| Session EO066 | Room: 604 |
| Recent advances in econometrics | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Seok Young Hong | Organizer: Seok Young Hong |
| E0746: S. Ge | |
| Augment large covariance matrix estimation with auxiliary network information | |
| E0565: S. Li, O. Linton, C. Dong, G. Connor | |
| A dynamic semiparametric characteristics-based model for optimal portfolio selection | |
| E1097: S. Yu, Y. Li, I. Nolte, S. Nolte | |
| Nonparametric range-based estimation of integrated variance with episodic extreme return persistence |
| Session EO045 | Room: 605 |
| Hawkes processes in econometrics and statistics | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Yoann Potiron | Organizer: Yoann Potiron |
| E0182: O. Scaillet, Y. Potiron, S. Yu | |
| Estimation of integrated intensity in Hawkes processes with time-varying baseline | |
| E0413: C. Aubrun, J.-P. Bouchaud, M. Benzaquen | |
| Modelling financial volatility with quadratic Hawkes | |
| E0652: Y. Potiron, V. Volkov | |
| Mutually exciting point processes with latency |
| Session EO152 | Room: 702 |
| Random matrix theory for complex data (virtual) | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Jesus Arroyo | Organizer: Cheng Wang |
| E0314: N. Parolya, T. Bodnar | |
| Resurrecting pseudoinverse: Asymptotic properties of large Moore-Penrose inverse with applications | |
| E1099: Y. Yang, H. Xiao Han | |
| Spiked eigenvalues of high-dimensional sample autocovariance matrices: CLT and applications | |
| E1189: A. Srakar | |
| Covariance and autocovariance estimation on a Liouville quantum gravity sphere in a functional context |
| Session EO192 | Room: 703 |
| Advances in time series and spatial data analysis | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Soudeep Deb | Organizer: Soudeep Deb |
| E0656: C.F. Jimenez Varon, Y. Sun, T.-H. Li | |
| Semiparametric estimation method for quantile coherence with an application to financial time series clustering | |
| E0688: P. Moraga | |
| Bayesian spatial modeling for data fusion adjusting for preferential sampling | |
| E0821: I. Dattner | |
| Recent advances in parameter estimation and model selection of differential equations with application for digital twins | |
| E1335: M. Podder | |
| A nonparametric method for the detection of changepoints in multivariate time series |
| Session EO220 | Room: 705 |
| Estimation for models with complex structural data | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Qian Lin | Organizer: Lixing Zhu |
| E1027: N. Zhou | |
| Semiparametric efficient estimation of genetic relatedness with double machine learning | |
| E1261: X. Li, Y. Liu, Y. Wu, L. Zhu | |
| Quantile regression with asynchronous longitudinal data | |
| E1272: Q. Lin, D. Huang, S. Tian | |
| Sliced inverse regression with large structural dimension |
| Session EC325 | Room: 02 |
| Non-parametric hypothesis testing | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Michele Guindani | Organizer: EcoSta |
| E0323: N. Koning | |
| The Surprising Power of Subgroup Selection in High-Dimensional Multiple Testing | |
| E0340: T. Lando, S. Legramanti | |
| Testing second-order stochastic dominance | |
| E0454: P. Oliveira, I. Arab, T. Lando | |
| Stochastic monotonicity of statistical functionals with testing application |
| Session EC328 | Room: 03 |
| Missing data | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Masayuki Hirukawa | Organizer: EcoSta |
| E0184: M. Chaouch, N. Laib | |
| Regression estimation for continuous time functional data processes with missing at random response | |
| E1156: A. Cosma, A. Kostyrka, G. Tripathi | |
| Missing endogenous variables in conditional moment restriction models | |
| E1160: Z. Feng, J. May, S. Adamovicz | |
| Approaches for handling missing values and their impacts on biological inferences: A molecular rate case study |
| Session EC304 | Room: 503 |
| Asset allocation | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Yifeng Guo | Organizer: EcoSta |
| Session EC280 | Room: 603 |
| Risk analysis | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Malika Hamadi | Organizer: EcoSta |
| E1151: N.H.U. Dewi, K. Syuhada | |
| Exploring and forecasting stochastic risk of payments series for loan and pension scheme | |
| E1205: M. Hamadi, A. Heinen, J. Juste | |
| Credit risk in microcredit markets | |
| E1149: S.-P. Feng | |
| Stock liquidity and value at risk for options |
| Session EC315 | Room: 606 |
| Econometric theory | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Teppei Ogihara | Organizer: EcoSta |
| E1104: U. Hassler, M. Hosseinkouchack | |
| Ratio tests using the Cauchy distribution: A simple principle | |
| E1022: S. Srisuma | |
| Uniform convergence rates for nonparametric estimators of a density function when the density has a known pole | |
| E1210: J.H. Lee | |
| Hypothesis testing for mediation effects in a generalized regression model |
| Session EC299 | Room: 701 |
| Stochastic volatility | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Toshiaki Watanabe | Organizer: EcoSta |
| E0256: Y. Bao, Y.L. Cheung | |
| Idiosyncratic volatility factor and macroeconomic risks | |
| E0374: M. Zaharieva | |
| Infinite sparse factor stochastic volatility model | |
| E1218: Y. Kurose | |
| Stochastic volatility model with range-based correction and leverage |
| Session EC190 | Room: 704 |
| Time series II | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Zudi Lu | Organizer: EcoSta |
| E0260: A. Freitas, A. Silva | |
| A new SSA-based procedure for detecting structural changes in a time series | |
| E0868: F. Papagni, D. Ferrari, G. Goracci | |
| Bias-reducing penalization for the Whittle likelihood | |
| E0261: P. Macedo, J. Duarte, M. Costa, M. Madaleno | |
| A two-stage maximum entropy approach for time series regression |
| Session EC268 | Room: 708 |
| Complex data analysis | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Ray-Bing Chen | Organizer: EcoSta |
| E0396: R. Guan, T.-I. Lin, W. Cheng | |
| Finite mixture model based on the GSMMGN family with several interval censoring | |
| E0701: C.-H. Yang | |
| Nested Grassmannians for dimensionality reduction with applications | |
| E1066: S. Lopez Pintado, X. Dai | |
| Tukey's depth for object data |
| Session EC267 | Room: 709 |
| High-dimensional data analysis | Wednesday 02.8.2023 18:00 - 19:15 |
| Chair: Sang-Yun Oh | Organizer: EcoSta |
| E0258: S. Wu | |
| Constrained approaches in learning high-dimensional sparse structures: Statistical optimality and optimization tools | |
| E0988: M. Demosthenous, C. Gatu, E. Kontoghiorghes | |
| Computational strategies for regression model selection in the high-dimensional case | |
| E1141: T. Honda | |
| Forward variable selection for ultra-high dimensional models |
| Parallel session K: EcoSta2023 | Thursday 03.8.2023 | 07:30 - 09:10 |
| Session EV269 | Room: 704 |
| Estimation and inference (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Daoji Li | Organizer: EcoSta |
| E0436: Y. Dong | |
| Doubly robust identification and estimation of the LATE model with a continuous treatment | |
| E1299: H. Kwon, Y. Liao, J. Choi | |
| Inference for low-rank models without rank estimation | |
| E0264: Y. Kim, S. Choi, S. Park, D. Bandyopadhyay, T. Choi | |
| Inverse weighted quantile regression with partially interval-censored data | |
| E0931: T. Moriyama | |
| A semiparametric approach in estimating sample maximum distribution |
| Session EO125 | Room: 03 |
| Modern statistical inference for complex data (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Meimei Liu | Organizer: Meimei Liu, Hongxiao Zhu |
| Session EO153 | Room: Virtual R01 |
| Interpretable statistics and ML for biological and biomedical data (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Wei Vivian Li | Organizer: Wei Vivian Li |
| Session EO130 | Room: Virtual R02 |
| Modern and innovative statistical learning methods for complex data (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Guannan Wang | Organizer: Guannan Wang |
| E0246: Z. Gu, S. Yu, G. Wang, L. Wang | |
| TSSS: A novel triangulated spherical spline smoothing for data distributed on complex surfaces | |
| E0455: L. Wang, G. Wang, Y. Wang | |
| Modeling and inference for 3D complex objects | |
| E0473: X. Song, K.K. Dobbin | |
| Evaluating biomarkers for treatment selection from reproducibility studies | |
| E0553: Y. Sun, J. Kang, C. Haridas, N. Mayne, A. Potter, C.-F.J. Yang, D. Christiani, Y. Li | |
| Penalized deep partially linear cox models with application to CT scans of lung cancer patients |
| Session EO118 | Room: 201 |
| High-dimensional mediation analysis (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Shuoyang Wang | Organizer: Yuan Huang |
| E1085: X. Cai, Y. Zhu, Y. Huang | |
| Comparisons of variable selection and inference methods in high-dimensional mediation analysis | |
| E1102: S. Wang, R. Li, Y. Huang | |
| Quantile mediation analysis with convoluted confounding effects via deep neural networks | |
| E1140: Y. Jiang, L. Xie, H. Zhang, M. Ray, C. Wu | |
| A joint approach to screen high dimensional mediators in epigenetic data with repeated outcomes | |
| E1223: Y. Im | |
| Bayesian high-dimensional mediation analysis incorporating neighborhood information |
| Session EO101 | Room: 203 |
| Causal inference: Methods and applications (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Subir Ghosh | Organizer: Subir Ghosh |
| E0670: S. Chen, Z. Jiang, P. Ding | |
| An instrumental variable method for point processes: generalized Wald estimation based on deconvolution | |
| E0802: Y. Zhu, V. Chernozhukov, K. Wuthrich | |
| A t-test for synthetic controls | |
| E0822: S. Pimentel, Y. Huang | |
| Covariate-adaptive randomization inference in matched designs | |
| E0877: L. Lei | |
| Double-robust two-way-fixed-effects regression for panel data |
| Session EO184 | Room: 503 |
| Bayesian methods and scalable computation for emerging studies (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Zhenke Wu | Organizer: Zhenke Wu |
| Session EO233 | Room: 506 |
| Advances in model-based clustering (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Yingying Zhang | Organizer: Shuchismita Sarkar |
| E0442: S.D. Tomarchio, A. Punzo, L. Bagnato | |
| Model-based clustering for tensor-variate data | |
| E0840: S. Columbu, N. Piras, J. Vermunt | |
| On the estimation of multilevel cross-classified latent class models | |
| E0603: Y. Zhang, V. Melnykov, I. Melnykov | |
| On model-based clustering of directional data with heavy tails and scatter | |
| E0637: R. Zheng, Y. Melnykov, Y. Zhang | |
| Model-based clustering on the spatial-temporal and intensity patterns of tornadoes | |
| E0775: Y. Melnykov, V. Melnykov, X. Zhu | |
| Transformation mixture modeling for skewed data groups with heavy tails and scatter |
| Session EO182 | Room: 603 |
| Recent advances in nowcasting (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Ekaterina Smetanina | Organizer: Ekaterina Smetanina |
| E0327: E. Ghysels, A. Babii, J. Striaukas, R. Ball | |
| Panel data nowcasting: The Case of price-earnings ratios | |
| E0770: M. Modugno, D. Cascaldi-Garcia, T. Ferreira | |
| Back to the present: Learning about the Euro Area through a now-casting model | |
| E0801: D. Giannone, F. Furno | |
| Nowcasting recession risk in the US and the Euro area |
| Session EO031 | Room: 604 |
| Recent advances in high dimensional time series (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Danna Zhang | Organizer: Danna Zhang |
| E0539: D. Zhang | |
| Robust estimation of high dimensional time series | |
| E0785: Y. Han | |
| CP factor model for dynamic tensors | |
| E0798: C. Zhang, D. Zhang | |
| Statistical inference of spectral density for high dimensional time series |
| Session EO163 | Room: 605 |
| Recent advances in stochastic modelling (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Takashi Owada | Organizer: Shuyang Bai |
| E1113: R. Zhang | |
| Quickest detection of the change of community via stochastic block models | |
| E1216: F. Fang, L. Forastiere, E. Airoldi, A. Ghasemianlangroodi | |
| Bayesian inference for causal effects under interference with a partially observed diffusion process on networks | |
| E1279: T. Owada, C. Hirsch, T. Kang | |
| Large deviations for the volume of k-nearest neighbor balls | |
| E1305: R. Xie, D. Wu | |
| Optimal transport-based domain adaptation for sensor data with application in smart manufacturing |
| Session EO029 | Room: 606 |
| Recent advances in time series trend and change point analysis (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Kin Wai Chan | Organizer: Kin Wai Chan |
| E1184: M.F. Leung, K.W. Chan | |
| Recursive nonparametric estimation: Principles, methods and applications | |
| E1236: M. Khismatullina, M. Vogt | |
| Estimation of the long-run error variance in nonparametric regression with time series errors | |
| E1271: C.H. Cheng, K.W. Chan | |
| A general framework for constructing locally self-normalized multiple-change-point tests | |
| E1254: K.W. Chan, Y.X. Wang | |
| Tight-difference-based centrosymmetric kernel estimators for long-run variance |
| Session EO157 | Room: 702 |
| Efficient methods for fitting complex network models (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Can Minh Le | Organizer: Can Minh Le |
| E0644: Y. Yuan | |
| High order joint embedding for multi level link prediction | |
| E0789: M.K. Shirani Faradonbeh | |
| Efficient online reinforcement learning policies for continuous environments | |
| E0800: G. Cantwell | |
| Approximate sampling and estimation of partition functions using neural networks | |
| E0910: J. Arroyo, J. Agterberg, Z. Lubberts | |
| Joint spectral clustering in multilayer degree-corrected stochastic blockmodels |
| Session EO037 | Room: 705 |
| Recent advances in high-dimensional statistics and machine learning (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Xiucai Ding | Organizer: Xiucai Ding |
| E0380: Z. Wang, X. Ding | |
| CLT for LSS of unnormalized sample covariance matrices when the dimension is much larger than the sample size | |
| E0606: Y. Shen, Y. Wu | |
| Empirical Bayes estimation: When does g-modelling beat f-modelling in theory (and in practice)? | |
| E0744: J. Huang | |
| Spiked tensor model | |
| E0902: Y. Zhong, C. Ma, Y. Gui | |
| Contrastive learning: An expansion and shrinkage perspective |
| Session EO127 | Room: 708 |
| Recent advances in functional data analysis (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Ruiyan Luo | Organizer: Ruiyan Luo |
| E0555: P. Reiss, B. Paul, E. Cui | |
| Continuous-time multivariate analysis: The transpose of functional data analysis | |
| E0377: P. Du, Q. Do, Y. Hong | |
| Functional degradation modeling of battery lives | |
| E0303: R. Luo | |
| General nonlinear function-on-function regression via functional universal approximation |
| Session EO248 | Room: 709 |
| Advances in dimension reduction: Theory and applications (virtual) | Thursday 03.8.2023 07:30 - 09:10 |
| Chair: Wenhui Sheng | Organizer: Wenhui Sheng |
| E0349: E. Christou | |
| Central quantile subspace and its extension to functional data | |
| E0512: L. Ni | |
| Pivot statistics for normal populations | |
| E0691: C. Ke | |
| Model-free feature screening for high-throughput semi-competing risks data with FDR control | |
| E0756: C.E. Lee, X. Zhang, L. Li | |
| Dimension reduction for tensor response regression models |
| Parallel session L: EcoSta2023 | Thursday 03.8.2023 | 09:20 - 11:00 |
| Session EO010 | Room: 02 |
| Latent variable models and applications | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Xiangbin Meng | Organizer: Gongjun Xu |
| E0831: K. Okada, K. Hijikata, M. Oka, K. Yamaguchi | |
| Variational Bayesian estimation in diagnostic classification models | |
| E0171: J. Zhu | |
| Network community detection using higher-order structures | |
| E0319: X. Meng | |
| MSAEM estimation for multidimensional four-parameter normal ogive models | |
| E0345: K. Yamaguchi | |
| Recent developments in variational inference algorithms for restricted latent class models |
| Session EO022 | Room: 03 |
| Early phase cancer clinical trial designs and reporting guidelines | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Yisheng Li | Organizer: Yisheng Li |
| E0663: A. Iasonos, J. OQuigley | |
| Randomized phase I clinical trials in oncology | |
| E0431: R. Lin | |
| Local continual reassessment methods for dose finding and optimization in drug-combination trials | |
| E1071: Y. Ibi, Y. Sano, T. Sato, K. Ueno, T. Omori | |
| Determining a follow-up period for cure rate estimation in an exploratory phase clinical trial | |
| E1183: C. Yap | |
| Guidance on statistical items in the SPIRIT and CONSORT extensions for early phase dose-finding clinical trials |
| Session EO071 | Room: 04 |
| Modeling longitudinal and time-to-event data: New directions and innovations | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Esra Kurum | Organizer: Esra Kurum |
| Session EO137 | Room: Virtual R01 |
| Recent advances in statistcal methods in biomedical applications | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Seung Jun Shin | Organizer: Seung Jun Shin |
| Session EO159 | Room: Virtual R02 |
| Modern machine learning methods dealing with a variety of data issues | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Xinyi Li | Organizer: Xinyi Li |
| E0456: G. Wang, L. Wang, S. Yu | |
| Nonparametric distributed learning of complex data | |
| E0991: L. Zhang | |
| Fair conformal prediction | |
| E1073: D. Li | |
| Contrastive inverse regression for dimension reduction | |
| E1175: S. Ranganathan, R. Karthikeyan, Q. Su | |
| Meta-analytic study of experimental data in the presence of missingness and unbalanced experimental factors |
| Session EO115 | Room: 102 |
| New developments in imaging and genetics using large scale studies | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Haochang Shou | Organizer: Haochang Shou |
| E0306: Y. Zhao, Y. Zhao | |
| Covariance-on-covariance regression | |
| E0668: B. Zhao | |
| Exploring cross-trait genetic architectures: Statistical models, computational challenges, and the BIGA platform | |
| E0667: Y.-P. Wang | |
| Integration of fMRI and genomics data with interpretable multimodal deep learning | |
| E0805: J. Jin, J. Zhan, J. Zhang, R. Zhao, J. O Connell, Y. Jiang, 2. Research Team, S. Buyske, C. Gignoux, C. Haiman, E. Kenny, C. Kooperberg, K. North, B. Koelsch, G. Wojcik, H. Zhang, N. Chatterjee | |
| ME-Bayes SL: Enhanced Bayesian polygenic risk prediction leveraging information across multiple ancestry groups |
| Session EO113 | Room: 201 |
| Econometrics and statistics on unobserved heterogeneity | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Katsumi Shimotsu | Organizer: Katsumi Shimotsu |
| E0409: K. Shimotsu, H. Kasahara, H. Matsuyama, S. Takeishi | |
| Testing for unobserved heterogeneity in censored duration models: EM approach | |
| E0419: S. Takeishi | |
| A shrinkage likelihood ratio test for high-dimensional subgroup analysis with a logistic-normal mixture model | |
| E0428: H. Kasahara, Y. Ahn | |
| Difference in differences with latent group structures | |
| E0602: T. Ishihara, K. Fusejima | |
| Identification and estimation of treatment effects in a linear factor model with fixed number of time periods |
| Session EO061 | Room: 203 |
| Causal mediation analysis and principal stratification | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Caleb Miles | Organizer: Caleb Miles |
| E1288: T. Nguyen | |
| Sensitivity analysis for principal ignorability violation in estimating complier and noncomplier average causal effects | |
| E1314: T. Kawahara, J. Young | |
| Estimands versus algorithms in studies with competing events and interest in treatment mechanism | |
| E0545: I. Diaz | |
| Mediation in causal survival analysis under competing risks using longitudinal modified treatment policies | |
| E1316: K. Rudolph, I. Diaz, N. Williams | |
| Causal mediation with instrumental variables |
| Session EO210 | Room: 503 |
| Large-scale Bayesian inference | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Mattias Villani | Organizer: Mattias Villani |
| E0404: P. Alquier, B.E. Cherief Abdellatif, C. Riou | |
| Rates of convergence in Bayesian meta-learning | |
| E0405: D. Nott, C. Drovandi, D. Frazier | |
| Improving the accuracy of marginal approximations in likelihood-free inference via localisation | |
| E0955: J. Chan, A. Poon, D. Zhu | |
| High-dimensional conditionally Gaussian state space models with missing data | |
| E1224: R. Kohn, D. Nott, D. Gunawan | |
| Flexible variational Bayes based on a copula of a mixture of normals |
| Session EO131 | Room: 506 |
| Complex space-time structures with modern spatio-temporal statistics | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Abhi Datta | Organizer: Stefano Castruccio |
| E0209: P. Ma | |
| Classes of multivariate and space-time power-law covariance functions | |
| E0480: J. Richards, M. Sainsbury-Dale, A. Zammit Mangion, R. Huser | |
| Neural Bayes estimators for fast and efficient inference with spatial peaks-over-threshold models | |
| E0536: Y. Cheng, W. Chang, R. Olson, J. Shin, S.-I. An | |
| Extract long-term trend from large-missing gap Atlantic meridional overturning circulation (AMOC) data | |
| E0773: T. Harris | |
| Multi-model ensemble analysis with neural network Gaussian processes |
| Session EO241 | Room: 603 |
| Recent advances in functional data/ longitudinal data | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Mengying You | Organizer: Mengying You |
| Session EO133 | Room: 604 |
| Recent contributions to nonparametric and semiparametric models | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Alexandra Soberon | Organizer: Alexandra Soberon |
| E0759: A. Musolesi | |
| Efficient estimation of a semiparametric panel data model with common factors and spatial dependence: Testing ETS | |
| E0177: J.M. Rodriguez-Poo, G. Keilbar, A. Soberon, W. Wang | |
| A projection based approach for interactive fixed effects panel data models | |
| E0272: V. Rodriguez-Caballero, E. Ruiz, G. Gonzalez-Rivera | |
| Modelling intervals of minimum/maximum temperature in the Iberian Peninsula | |
| E0543: D. Henderson, J. Jiang | |
| Testing for relevance of partially parametric models with parametric nulls |
| Session EO106 | Room: 605 |
| Statistical modeling of relation data | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Tianxi Li | Organizer: Tianxi Li |
| E0288: W. Zhou, Y. Zhang, W. Du | |
| Nonparametric inference on network effects of general relationship network data | |
| E0356: A.Y. Zhang | |
| Fundamental limits of spectral clustering in stochastic block models | |
| E0495: K. Chen, J. Lu | |
| Nonparametric link prediction for networks and Bipartite graph | |
| E0752: M. Thirkettle | |
| Identification and estimation of network statistics with missing link data |
| Session EO310 | Room: 606 |
| Multivariate problems for structured dependent data II | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Michal Pesta | Organizer: Michal Pesta, Matus Maciak |
| E1019: K. Vuk, H. Dehling, M. Wendler | |
| Weighted change-point tests for short-range dependent data | |
| E1157: V. Witkovsky | |
| Numerical inversion of characteristic functions for exact multivariate statistical inference | |
| E0421: D. Hlubinka, Z. Hlavka | |
| Functional ANOVA based on Fourier transform of distribution | |
| E0293: M. Maciak | |
| Instabilities in time-dependent implied volatility functional profiles |
| Session EO188 | Room: 701 |
| Topics in graphical modeling | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Sang-Yun Oh | Organizer: Sang-Yun Oh |
| E1167: G. Park | |
| Optimal backward-learning approach for Gaussian linear structural equation models | |
| E0313: M. Kolar | |
| Confidence sets for causal discovery | |
| E0774: J.-H. Won | |
| High-performance computing for sparse graphical models | |
| E0600: S.-Y. Oh | |
| FROSTY: A high-dimensional scale-free Bayesian network learning method |
| Session EO039 | Room: 702 |
| Recent advances in experimental design and analysis | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Qian Xiao | Organizer: Qian Xiao |
| E0828: Y. Wang, Q. Xiao, S. Liu | |
| Construction of orthogonal-maxpro latin hypercube designs | |
| E0923: Q. Xiao | |
| Maximum one-factor-at-a-time designs for screening in computer experiments | |
| E1129: Q. Zhang | |
| Uncertainty quantification of optimal decision in curing process simulation | |
| E1192: S. Liu, Y. Wang, Q. Xiao | |
| Construction of space-filling Latin hypercube designs with flexible run sizes |
| Session EO236 | Room: 703 |
| Statistical network analysis I | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Keith Levin | Organizer: Keith Levin |
| E0777: J. Cape | |
| On network modularity statistics in connectomics and schizophrenia | |
| E0893: R. Lunde, L. Levina, J. Zhu | |
| Conformal prediction for network regression | |
| E0899: D. Asta | |
| Geometric inference via graph Laplacians | |
| E0908: M. Tang, Y. Zhang | |
| Perturbation analysis of randomized SVD and its applications to high-dimensional statistics |
| Session EO162 | Room: 704 |
| Modern development in longitudinal/survival data analyses | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Hyunkeun Cho | Organizer: Hyunkeun Cho |
| E0468: Y. Cho, J. Park | |
| Estimation of heterogeneous treatment effect using random forests for competing risks data | |
| E0308: M. Lee | |
| Statistical approach to handling measurement issues in self-reported data that are longitudinally collected | |
| E0410: Y. Gwon, J. Meza | |
| Bayesian Conway-Maxwell-Poisson regression for longitudinal count data | |
| E0662: H. Cho, D. Kuwaye, D.-E. Lafontant | |
| A new perspective on unsupervised learning in longitudinal studies |
| Session EO034 | Room: 705 |
| Recent advance of high-dimensional statistics | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Quefeng Li | Organizer: Quefeng Li |
| E0187: K. Zhang, B. Brown, X.-L. Meng | |
| BELIEF in dependence: Leveraging atomic linearity in data bits for rethinking generalized linear models | |
| E0215: J. Chen | |
| Network detection through odds ratio model | |
| E0443: X. Guo | |
| Inference for high-dimensional linear models with locally stationary error processes | |
| E0629: H. Jiang, Q. Li, J. Lin, F.-C. Lin | |
| Classification of competing risks under a semiparametric density ratio model with transition of markers |
| Session EO229 | Room: 708 |
| New advances in functional data analysis | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Yuhang Xu | Organizer: Jane-Ling Wang |
| E0175: C. Zhu, J.-L. Wang | |
| Testing homogeneity: The trouble with sparse functional data | |
| E0193: Q. Zhong, S. Hao, S.-C. Lin, J.-L. Wang | |
| Dynamic modelling for multivariate functional and longitudinal data | |
| E0379: K.-Y. Lee, L. Li, B. Li | |
| DAG learning from multivariate functional data | |
| E0914: X. Ding | |
| Approximation, estimation and inferential theory for locally stationary functional time series |
| Session EO016 | Room: 709 |
| Methods for causal inference, precision medicine and dimension reduction | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Zheng Zhang | Organizer: Shujie Ma |
| E0275: Z. Qi | |
| STEEL: Singularity-aware reinforcement learning | |
| E0401: Z. Zhang | |
| Casual inference of general treatment effects using neural networks with a diverging number of confounders | |
| E0481: Y. Matsushita, H. Chiang, T. Otsu | |
| Regression adjustment in randomized controlled trials with many covariates | |
| E0919: W. Luo | |
| On efficient dimension reduction with respect to the interaction between two response variables |
| Session EP001 | Room: Poster session II |
| Poster session II | Thursday 03.8.2023 09:20 - 11:00 |
| Chair: Cristian Gatu | Organizer: EcoSta |
| E0259: J. Pena Rivera, I. Da Luz Santana | |
| A longitudinal study of the impact of hurricanes in quality of life on women diagnosed with gynecological cancer | |
| E0361: G. Kundhi, P. Rilstone | |
| New second-order asymptotic methods for nonlinear models | |
| E0650: I.Y. Baek, S. Jo, J.O. Kim | |
| One class classification using Bayesian optimization | |
| E0715: J.I. Lee, S.I. Jo, J.O. Kim | |
| Beta regression models: Practical analyses with KNHANES 2013-2015 data and Covid-19 data | |
| E1013: H. Lee, Y. Cho | |
| Subgroup analysis in the observational studies | |
| E1057: E.-K. Lee | |
| Tree-structured clustering model using projection pursuit method and their explanation | |
| E1139: J. Park | |
| Improving multiple linear regression with random forest using Mahalanobis distance | |
| E1284: S. Ahn | |
| t-distributed stochastic neighborhood embedding of tensor data with two applications |
| Parallel session N: EcoSta2023 | Thursday 03.8.2023 | 13:40 - 14:55 |
| Session EO211 | Room: 02 |
| Advances in statistics | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Yang Ni | Organizer: Yang Ni |
| Session EO214 | Room: 03 |
| Recent developments in complex data analysis | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Xin He | Organizer: Xin He |
| E0972: L. Zhang, W. Zhou, H. Wang | |
| Integrative group factor model for variable clustering on temporally dependent data: Optimality and algorithm | |
| E0974: Q. Zhu, S. Tan, Y. Zheng, G. Li | |
| Quantile autoregressive conditional heteroscedasticity | |
| E1109: X. He, Y. Deng, S. Lv | |
| Efficient learning of nonparametric directed acyclic graph with statistical guarantee |
| Session EO309 | Room: Virtual R01 |
| Recent developments in high-dimensional change point analysis | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Hyeyoung Maeng | Organizer: Hyeyoung Maeng |
| E0435: Z. Zhao | |
| High-dimensional dynamic pricing under non-stationarity: Learning and earning with change-point detection | |
| E0683: Y. Chen, M. Li, T. Wang, Y. Yu | |
| Robust high-dimensional change point detection under heavy tails | |
| E1111: M. Londschien, P. Buehlmann, S. Kovacs | |
| Random forests for change point detection |
| Session EO013 | Room: 102 |
| Recent developments in Bayesian methods and high-dimensional statistics | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Shouzheng Chen | Organizer: Catherine Liu |
| E1209: C. Zhong, Z. Ma, X. Zhang, C. Liu | |
| Non-segmental Bayesian detection of multiple change-points | |
| E1204: X. Zhang | |
| Estimation of Tucker tensor factor models for high-dimensional higher-order tensor observations | |
| E1297: S. Chen, C. Zhong, X. Zhang | |
| Nonparametric transformation models for doubly censored survival data: A Bayesian approach |
| Session EO058 | Room: 201 |
| Causal inference | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Yen-Tsung Huang | Organizer: Yen-Tsung Huang |
| E0738: B. Sun, Z. Liu, E. Tchetgen Tchetgen | |
| G-estimation with invalid instrumental variables | |
| E1064: L.-Y. Chen, S. Lee | |
| Sparse quantile regression | |
| E1119: J.-C. Yu, Y.-T. Huang | |
| Separable effects under semicompeting risks |
| Session EO219 | Room: 203 |
| Checking for model structural change in high-dimensional data | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Tiejun Tong | Organizer: Lixing Zhu |
| E0402: J. Huang, J. Wang, L. Zhu, X. Zhu | |
| Multiple change point detection in tensors | |
| E0835: Q. Jiang | |
| Testing the martingale difference hypothesis in high dimension | |
| E1268: W. Zhao, L. Zhu, F. Tan | |
| Multiple change point detection for high-dimensional data |
| Session EO069 | Room: 503 |
| Recent advances in Bayesian analysis | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Jouchi Nakajima | Organizer: Jouchi Nakajima |
| E0424: T. Kunihama | |
| Bayesian analysis of verbal autopsy data using probit model with age- and sex-dependent association between symptoms | |
| E0968: K. Irie, S. Sugasawa, Y. Hamura | |
| Gibbs sampler for matrix generalized inverse Gaussian distributions | |
| E0737: N. Wichitaksorn, R. Khanthaporn | |
| Bayesian estimation of R-vine Copula with Gaussian-mixture GARCH margins |
| Session EO110 | Room: 506 |
| Recent advances in high-dimensional econometrics | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Qingliang Fan | Organizer: Degui Li |
| E0393: Q. Fan | |
| On the instrumental variable estimation with many weak and invalid instruments | |
| E0623: T. Cheng | |
| GMM estimation for high-dimensional panel data models | |
| E0730: W. Wang, Y. Zhang, D. Lim | |
| A conditional linear combination test with many weak instruments |
| Session EO043 | Room: 603 |
| Advances in large-scale Inference | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Bradley Rava | Organizer: Bradley Rava, Peter Radchenko |
| E0697: P. Radchenko | |
| Large scale partial correlation screening | |
| E0771: B. Rava | |
| Unrestricted hypothesis testing | |
| E0855: W. Chen, B. Rava, N. Ho-Nguyen | |
| Value-at-Risk forecasts under misspecified conditional models |
| Session EO042 | Room: 604 |
| Cryptocurrency, renewable energy and efficiency | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Artem Prokhorov | Organizer: Artem Prokhorov |
| E1147: T. Kurita, J.L. Castle | |
| Econometric modelling of cryptocurrency prices | |
| E1241: X. Shi, Y. Fan, Y. Okar | |
| Iterative distributed multinomial logistic regression | |
| E1237: A. Prokhorov | |
| Dependence in models of production: New estimators and techniques |
| Session EO142 | Room: 605 |
| Statistical inference for nonstationary data structures | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Claudio Durastanti | Organizer: Alessia Caponera |
| E0220: D. Wang | |
| Change point inference in high-dimensional regression models under temporal dependence | |
| E0578: F. Spoto, A. Caponera, P. Brutti | |
| Spherical autoregressive multiple change-point detection | |
| E0761: S. Basu, S. Subbarao | |
| Graphical models for nonstationary time series |
| Session EO084 | Room: 606 |
| Advances in business analytics | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Amanda Chu | Organizer: Amanda Chu |
| E0960: S.H. Chan, A. Chu, M. So | |
| Graphical copula GARCH modelling with dynamic conditional dependence | |
| E1028: T. Chan, M. So, A. Chu | |
| A semi-parametric multidimensional and longitudinal item response model with mixed data type | |
| E1134: J.N.L. Chan, A. Chu, M. So | |
| The development of an automatic speech analytics program to detect the level of stress burden |
| Session EO232 | Room: 701 |
| Recent developments in econometric theory | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Cy Sin | Organizer: Cy Sin |
| E0560: T.-C. Lai, J.-H. Shih, Y.-H. Chen | |
| Nonparametric and semiparametric estimation of upward rank mobility curves | |
| E0493: J.-C. Liao | |
| Testing the impacts on inefficiency in a semiparametric stochastic frontier model | |
| E0793: S.-Y. Yin | |
| Inference on three-pass regression filter with high-dimensional target variables |
| Session EO097 | Room: 702 |
| Modern statistical methods for longitudinal and imaging data | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Frederic Ferraty | Organizer: Xinyuan Song |
| Session EO235 | Room: 703 |
| Statistical network analysis II | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Avanti Athreya | Organizer: Avanti Athreya |
| E0631: D. Choi | |
| Estimating the prevalence of peer effects in network experiments | |
| E0881: K. Levin | |
| Estimating network-mediated causal effects via spectral embeddings | |
| E0906: Z. Lubberts, A. Athreya, C. Priebe, Y. Park | |
| Beyond the adjacency matrix: Random line graphs and inference for networks with edge attributes |
| Session EO213 | Room: 704 |
| Recent advances in financial big data analysis | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Minseok Shin | Organizer: Minseok Shin |
| E1007: M. Shin, D. Kim | |
| Robust high-dimensional time-varying coefficient estimation | |
| E1017: M. Oh, D. Kim, Y. Wang | |
| Robust realized integrated beta estimator with application to dynamic analysis of integrated beta | |
| E1024: D. Chun | |
| Forecasting returns and optimizing global portfolios with machine learning: The Korean and U.S. stock markets |
| Session EO038 | Room: 705 |
| Recent advances in clustering and high dimensional data analysis | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Sanjeena Dang | Organizer: Weixin Yao |
| E0787: S. Dang, A. Payne, A. Silva, S. Rothstein, P. McNicholas | |
| Clustering high-dimensional count data | |
| E0795: F. Tan | |
| Weighted residual empirical processes, martingale transformations, and model checking for regressions | |
| E0794: B. Franczak | |
| Recent developments in using mixtures of multivariate asymmetric distributions for classification |
| Session EO040 | Room: 708 |
| Statistical methods for functional observations | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Ci-Ren Jiang | Organizer: Ci-Ren Jiang |
| E0262: E. Lila | |
| Interpretable discriminant analysis for functional data supported on random non-linear domains | |
| E0472: A. Petersen, X. Liu | |
| Truncated estimation in functional generalized linear regression models | |
| E0651: C.-R. Jiang, E. Lila, J.-L. Wang, J. Aston | |
| Eigen-adjusted functional principal component analysis |
| Session EO060 | Room: 709 |
| New challenges and insights in high-dimensional statistics | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Wei Luo | Organizer: Lingzhou Xue |
| E0445: L. Zhou, B. Wang, H. Zou | |
| Sparse convoluted rank regression in high dimensions | |
| E0552: S. Yang | |
| New tests for high-dimensional two-sample mean problems with consideration of correlation structure | |
| E0871: C. Li | |
| Causal structural learning and application in epidemiology |
| Session EC322 | Room: 04 |
| Censored data | Thursday 03.8.2023 13:40 - 14:55 |
| Chair: Takeshi Emura | Organizer: EcoSta |
| E0469: S. Park, S. Choi, Z. Jin, W. Lu | |
| Rank-based regression for doubly interval-censored data | |
| E1135: R. Cao, A. Lopez-Cheda, B. Pineiro-Lamas | |
| Single-index mixture cure models: An application to a study of cardiotoxicity in breast cancer patients | |
| E1155: Y.-K. Tseng | |
| Design on three-arm noninferiority trials using parametric and semiparametric methods for censored survival data |
| Parallel session O: EcoSta2023 | Thursday 03.8.2023 | 15:25 - 17:05 |
| Session EV274 | Room: Virtual R02 |
| Modelling and forecasting | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Esra Kurum | Organizer: EcoSta |
| E1005: B. Kozyrev, O. Holtemoeller | |
| Forecasting economic activity with a neural network in uncertain times: Application to German GDP | |
| E1094: K. Heinisch | |
| Step by step: A quarterly evaluation of EU commissions' GDP forecasts | |
| E1136: A. Congedi, S. De Iaco, S. Maggio | |
| A term structure dynamic model with correlated residuals: A comparative analysis | |
| E0296: G.A. Tsiatsios, I. Kollias, E. Melas, J. Leventides, C. Poulios | |
| Some first results from an agent-based model of consumer demand |
| Session EO017 | Room: 02 |
| Text data | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Ana Colubi | Organizer: Erricos Kontoghiorghes |
| E1312: A. Colubi, L. Kontoghiorghes | |
| HiTEc: Exploiting text data in applications | |
| E1174: L. Kontoghiorghes, A. Colubi | |
| Measuring and comparing the thematic prevalence using a parametric and distribution-free bootstrap two-sample test | |
| E1212: L.-J. Kao, C.-C. Chiu, C.-M. Wu, T.-N. Chien, C. Li | |
| Predicting ICU readmission with a hybrid BERTopic-LSTM approach on electronic health records |
| Session EO132 | Room: Virtual R01 |
| Extreme risk measures estimation in various attraction domains | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Antoine Usseglio-Carleve | Organizer: Antoine Usseglio-Carleve |
| E0621: A. Daouia, S. Padoan, G. Stupfler | |
| Extreme expectile estimation for short-tailed data | |
| E0653: C. Yan, S. Girard, T. Opitz, A. Usseglio-Carleve | |
| Analysis of variability in extremes | |
| E0711: J. El Methni, S. Girard | |
| A refined extreme quantiles estimator for Weibull tail-distributions | |
| E0834: A. Usseglio-Carleve, A. Daouia, G. Stupfler | |
| Bias- and variance-corrected asymptotic Gaussian inference about extreme expectiles |
| Session EO218 | Room: 603 |
| Forecast combination | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Andrey Vasnev | Organizer: Andrey Vasnev |
| E0452: R. Thompson, A. Vasnev, Y. Qian | |
| Global combinations of expert forecasts | |
| E0820: R. Ouysse, A. Vasnev | |
| Factor models and forecast combinations | |
| E0655: W. Wang | |
| Optimal model averaging for single-index models with divergent dimensions | |
| E0477: A. Vasnev, A. Clements | |
| Forecast combination puzzle in the HAR model |
| Session EO080 | Room: 604 |
| Recent developments in time series econometrics | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Cy Sin | Organizer: Cy Sin |
| E0726: Y.-F. Gau, H. Chang | |
| Risk-return trade-off in the Bitcoin market: Downside risk and sentiment | |
| E0583: H. Kew | |
| Binary choice models with multiple integrated predictors | |
| E0736: Y. Pan, C.-K. Ing, C. Sin | |
| Prediction for multivariate time series models with deterministic time trends | |
| E0809: C. Sin | |
| Re-balancing hedge position with statistics of hedge ratios: Concepts and applications |
| Session EO147 | Room: 605 |
| Probability and stochastic geometry with statistical applications | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Claudio Durastanti | Organizer: Claudio Durastanti |
| E0556: G. Bet | |
| Detecting a late changepoint in a growing network | |
| E0592: N. Turchi, G. Bonnet, Z. Kabluchko | |
| The volume of random Beta polytopes in high dimensions | |
| E0628: V. Cammarota, D. Marinucci, M. Rossi | |
| Lipschitz-Killing curvatures for arithmetic random waves | |
| E0827: C. Durastanti, D. Marinucci, A.P. Todino, S. Bourguin | |
| Spherical Poisson waves |
| Session EO095 | Room: 606 |
| Advances in complex time series analysis | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Weilin Chen | Organizer: Clifford Lam |
| E0199: T. Wang | |
| Sparse change detection in high-dimensional linear regression | |
| E0358: W. Chen, C. Lam | |
| Rank and factor loadings estimation in time series tensor factor model by pre-averaging | |
| E0447: Z. Cen, C. Lam | |
| Imputation for tensor time series | |
| E0484: M. Knight, M. Nunes, J. Hargreaves | |
| Adaptive wavelet domain principal component analysis for nonstationary time series |
| Session EO102 | Room: 702 |
| Repeated measures, FDA, nonparametric regression, and regularized t-test | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Yuedong Wang | Organizer: Yuedong Wang |
| E0236: A. Roy, T. Opheim | |
| Linear models for multivariate repeated measures data | |
| E0300: T. Tong | |
| Regularized t distribution: Definition, properties and applications | |
| E1177: H. Lin | |
| Communication-efficient distributed portfolio selection strategy | |
| E0297: W. Dai, X. Tong, T. Tong | |
| Optimal-$k$ difference sequence in nonparametric regression |
| Session EO024 | Room: 703 |
| Statistical network analysis III | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Joshua Cape | Organizer: Joshua Cape |
| E0485: A. Mele, C.-P. Georg | |
| A strategic model of software dependency networks | |
| E0780: V. Lyzinski, A. Saxena | |
| Lost in the shuffle: Testing power in the presence of errorful network vertex labels | |
| E0889: S. Sengupta | |
| Two generalizable strategies for scalable inference from network data | |
| E0905: A. Athreya, Z. Lubberts, C. Priebe, Y. Park | |
| Discovering underlying dynamics in time series of networks |
| Session EO168 | Room: 705 |
| Recent advances in high-dimensional and dependent data analysis | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Ching-Kang Ing | Organizer: Ching-Kang Ing |
| E0257: S.-H. Yu | |
| A negative moment bound for integrated autoregressions with polynomial time trend and its applications | |
| E0540: P. Peng, H. Chiou, H.-H. Huang, C.-K. Ing | |
| Feature selection for high-dimensional heteroscedastic regression models | |
| E0833: S. Imori, C.-K. Ing | |
| Importance weighted orthogonal greedy algorithm with estimated weight function | |
| E0947: C.-K. Ing | |
| Model selection for unit-root time series with many predictors |
| Session EO311 | Room: 708 |
| High-dimensional data analysis with cluster structure | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Antonio Elias | Organizer: Antonio Elias |
| E0412: A. Caro Navarro, M. Camacho, D. Pena | |
| Dynamic factor models with cluster structure | |
| E0467: C. Tang, H.L. Shang, Y. Yang | |
| Clustering and forecasting multiple functional time series | |
| E0554: B. Pulido Bravo, R. Lillo, A. Franco-Pereira | |
| Clustering multivariate functional data: An application of the multivariate epigraph and hypograph indexes | |
| E0861: A. Mendez Civieta, J. Goldsmith, Y. Wei | |
| Quantile based functional principal component analysis |
| Session EO087 | Room: 709 |
| Recent developments in insurance statistics | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Sangyeol Lee | Organizer: Sangyeol Lee |
| E0946: J.-K. Woo, E.C.K. Cheung, R. Feng, H. Liu | |
| What is the average surplus before ruin? | |
| E0961: J.Y. Ahn | |
| Tractable Poisson time-series models for experience rating | |
| E1002: K. Park, J.Y. Ahn, R. Oh, Y. Lu, D. Zhu | |
| Attention is not not not explanation: With a focus on insurance ratemaking | |
| E1058: R. Oh | |
| A multivariate compound dynamic contagion process for infectious events |
| Session EC292 | Room: 03 |
| Biostatistics | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Michelle Miranda | Organizer: EcoSta |
| Session EC276 | Room: 04 |
| Survival analysis | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Yoann Potiron | Organizer: EcoSta |
| E0365: I. Arab, T. Lando, P. Oliveira | |
| Comparing aging patterns of k-out-of-n systems using second-order stochastic dominance | |
| E1152: C.-C. Wen | |
| Analysis of errors-in-variables competing risks data in discrete time | |
| E1292: C.H. Lee | |
| Estimating time-varying treatment effects on restricted mean survival time in large patient databases | |
| E1200: M.S. Panwar | |
| Bayesian joint modelling of longitudinal and competing risks data with cause dependent masking |
| Session EC272 | Room: 102 |
| Multivariate statistics | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Sara Lopez Pintado | Organizer: EcoSta |
| E0202: R.G. Agustin, M.D. Lucagbo | |
| Random-covariate-dependent rectangular reference regions under multivariate normality | |
| E1154: G. Van Bever, G. Louvet | |
| The influence function of scatter halfspace depth | |
| E1243: R. Tasaka, R. Shimmura, J. Suzuki | |
| Spacing test for generalized lasso with full row rank of D: Fused lasso and trend filtering | |
| E1249: N. Deliu, L. Brunero | |
| Probabilistic and distance-based approaches for computing multivariate highest-density regions |
| Session EC283 | Room: 201 |
| Non- and semi-parametric methods | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Kou Fujimori | Organizer: EcoSta |
| E0281: R. Le Guevel, F. Lavancier | |
| Non-parametric inference of spatial birth-death-move processes | |
| E1145: P. Mozharovskyi, J. Ivanovs | |
| Distributionally robust halfspace depth | |
| E1195: Y. Okamoto, S. Imai | |
| Variance properties of local polynomial density estimators at the boundary: Application to manipulation testing | |
| E1309: G. Shen, Y. Jiao, Y. Lin, J. Horowitz, J. Huang | |
| Nonparametric estimation of non-crossing quantile regression process with deep ReQU neural networks |
| Session EC284 | Room: 203 |
| Applied econometrics II | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Masayuki Hirukawa | Organizer: EcoSta |
| E1315: K. Pericleous, P. Kosmas, A. Theocharous, E. Ioakimoglou, H. Andreev | |
| Exploring profitability changes in hospitality industry: An econometric and statistical perspective | |
| E0440: C.H. Tang, K.Y. Leung | |
| Can we have the cake and eat it too? The case for the top-floor units as a status good and an investment | |
| E1014: T. Tichy | |
| Impact of various weather data on leisure sales | |
| E1208: M. Raude | |
| Firm behaviour in the European carbon market: Latent profile analysis on network indicators of transactions |
| Session EC318 | Room: 503 |
| Bayesian modelling and inference | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Yasuhiro Omori | Organizer: EcoSta |
| E0317: S. Migliorati, A. Ongaro, R. Ascari | |
| A generalization of the Dirichlet-multinomial regression model for microbiome counts | |
| E0611: Y.-W. Chang, C.-X. Yang | |
| Bayesian inference for differential item functioning detection in a multiple-group IRT tree model | |
| E1081: K. Dayaratna, J. Crosson, C. Hubbard | |
| Closed form Bayesian inferences for binary logistic regression with applications to American voter turnout | |
| E1146: D.K. Hermanto | |
| Beta four parameter generalized linear mixed model using a Bayesian approach to predict paddy productivity |
| Session EC279 | Room: 506 |
| Machine learning in economics and finance | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Jeffrey Bohn | Organizer: EcoSta |
| E0740: J. Bohn | |
| Boosting time-series prediction performance for inflation indicators | |
| E1088: A. Zhao, S. Jiang | |
| Corporate bond return prediction: An ensemble learning approach | |
| E0357: W. Orzeszko, D. Piotrowski | |
| Determinants of adoption of robo-advisory in banking services | |
| E1009: B. Jia, H.Y. Wong | |
| Deep impulse control |
| Session EC295 | Room: 701 |
| Financial econometrics II | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Zudi Lu | Organizer: EcoSta |
| E0214: L.A. Arteaga Molina, J.M. Rodriguez-Poo | |
| Testing beta constancy in capital asset pricing models | |
| E1126: J. Kurka | |
| Distributional asymmetries and currency returns | |
| E1229: S. Kwok, R. Jarrow | |
| A study on asset price bubble dynamics: Explosive trend or quadratic variation? | |
| E1215: A. Heinen, S. Lee | |
| Measuring systemic risk with non-exchangeable dependence |
| Session EC296 | Room: 704 |
| Econometric and statistical modelling | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Jouchi Nakajima | Organizer: EcoSta |
| E1165: T. Matsumoto, T. Kamai, Y. Kanazawa | |
| Reexamination of bargaining power in the distribution channel under possible price pass-through behaviors of retailers | |
| E1036: F. Cortese, E. Lindstrom, P. Kolm | |
| What drives cryptocurrency returns? A sparse statistical jump model approach | |
| E1045: J. Striaukas | |
| Nowcasting GDP with factor-augmented high-dimensional MIDAS regression | |
| E1329: A. Maheshwari | |
| On the estimation of parameters of fractional Poisson processes |
| Session EP327 | Room: Poster session III |
| Poster Session III | Thursday 03.8.2023 15:25 - 17:05 |
| Chair: Cristian Gatu | Organizer: EcoSta |
| E1242: Z. Wang, Y. Zheng, R. Yoshino | |
| Empirical analysis on characteristics of Japanese consumer behaviors based on the consumption values | |
| E1246: R.-H. Chung, D.D. Onthoni, K.-Y. Lan, T.-H. Huang, Y.-E. Chen | |
| Utilizing latent space representation for clustering chronic kidney disease subtypes via electronic health records | |
| E0311: S. Jeong, M. Park | |
| Simultaneous component decomposition and anomaly detection in financial time series | |
| E0725: H. Lim, E. Lee, J.Y. Park | |
| Classifying Alzheimers Disease patients and identifying related BOLD signals using penalized logistic regression | |
| E0338: Y.H. Um, M.K. Lee | |
| Setting of optimal process conditions for a diaphragm rate of change using DOE | |
| E0836: I. Ji, E. Lee | |
| Investigating resting-state fMRI for Alzheimer's disease identification through functional data analysis | |
| E1330: M.-S. Oh | |
| Prediction of PM10 in Seoul, Korea using Bayesian networks |