KEYNOTE TALKS (UTC+1)
| Keynote talk I | Wednesday 17.7.2024 | 09:00 - 09:50 | Room: Auditorium |
| Statistical generative learning leveraging pretrained large models | |||
| Speaker: J. Huang | Chair: Lixing Zhu | ||
| Keynote talk II | Wednesday 17.7.2024 | 15:40 - 16:30 | Room: Auditorium |
| Post-mortem interval: A functional data analysis for criminology | |||
| Speaker: F. Ferraty Co-authors: D. Pigoli, J. Aston, A. Mazumder, M. Hall, C. Richards | Chair: Catherine Liu | ||
| Keynote talk III | Friday 19.7.2024 | 16:45 - 17:35 | Room: Auditorium |
| Identifying impulse responses with instrumental variables | |||
| Speaker: M.H. Seo Co-authors: B. Koo, S.J. Lee | Chair: Tommaso Proietti | ||
PARALLEL SESSIONS (UTC+1)
| Parallel session B: EcoSta2024 | Wednesday 17.7.2024 | 10:20 - 12:00 |
| Session EO010 | Room: 102 |
| Statistics and machine learning for financial time series and insurance data | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Yuning Zhang | Organizer: Boris Choy |
| A0888: L. Cai, L. Jin | |
| A new test for checking stationarity in variance for nonlinear time series with a trend | |
| A0891: C. Wang, M.-N. Tran, R. Gerlach, R. Kohn | |
| DeepVol: A pre-trained universal asset volatility model | |
| A0928: N. Wichitaksorn | |
| Portfolio optimization through regular vine copula model and computational intelligence method | |
| A0878: Y. Zhang, B. Choy, W.Y. Chen, T.K. Siu | |
| Bayesian bi-directional self-exciting threshold autoregressive model and the application in loss reserving |
| Session EO157 | Room: 103 |
| Advances in regression and stochastic frontier analysis with panel data | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Taining Wang | Organizer: Kai Sun, Taining Wang |
| Session EO019 | Room: 104 |
| Recent development in high-dimensional inference and modeling | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Wenbo Wu | Organizer: Wenbo Wu |
| A0334: D. Li | |
| CoxKnockoff: Controlled feature selection for the Cox model using knockoffs | |
| A0830: C. Ke | |
| Reimaging semi-competing risks data analysis: Enhancing variable selection with preliminary dimension reduction | |
| A0910: T. Zu, Z. Zhao, Y. Yu | |
| FDR control for high dimensional quantile variable selection | |
| A0591: Y. Zhang, A. Qu, Y. Yuan, Q. Xu, F. Xue, K. Wei | |
| Mediation analysis with ultra-high dimensional confounders for the study on geriatric depression and Alzheimer's disease |
| Session EO018 | Room: 105 |
| Current statistical innovations in industrial and applied statistics | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Tsung-Jen Shen | Organizer: Chang-Yun Lin, Tsung-Jen Shen |
| A0917: S.-H. Huang | |
| Robust group testing for prevalence estimation against uncertain test error mechanisms | |
| A0964: C.-Y. Lin | |
| Cause-and-effect diagram-based supersaturated designs | |
| A0946: T.-C. Cheng | |
| Confirmatory analysis to identify relative importance of regressors for the linear regression model | |
| A0918: T.-J. Shen | |
| Predicting encounter distance for new species discovery |
| Session EO028 | Room: 106 |
| Advances of statistical learning methods and their applications | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Xuan Bi | Organizer: Xuan Bi |
| Session EO140 | Room: 108 |
| Frontiers at the intersection of statistics and machine learning | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Zhenke Wu | Organizer: Zhenke Wu |
| Session EO204 | Room: 109 |
| Theory-driven machine learning methods | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Ben Dai | Organizer: Ben Dai |
| A0456: G. Wang, J. Ding, Y. Yang | |
| Model privacy: A unified framework to understand model stealing attack and defense | |
| A0514: Y. Gao, B. Dai | |
| Word-level maximum mean discrepancy regularization for word embedding | |
| A0615: H. Xue, H. Liao, W. Pan | |
| Inferring causal direction between two traits using R-squared with application to transcriptome-wide association studies | |
| A0949: C. Liu | |
| Non-asymptotic bounds for adversarial excess risk under misspecified models |
| Session EO170 | Room: 110 |
| Recent developments in design and analysis of experiments | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Chenlu Shi | Organizer: Chenlu Shi |
| A0159: H. Wang | |
| Subsampling and rare events data beyond binary responses | |
| A0400: Q. Xiao, Y. Wang, S. Liu | |
| Construction of orthogonal-MaxPro Latin hypercube designs | |
| A0535: W. Zheng | |
| Design inspired Thompson sampling | |
| A0689: Y. Li, L. Kang | |
| Kernel discrepancy-based rerandomization for controlled experiments |
| Session EO054 | Room: 111 |
| Advances in statistical methods for biological data and health informatics | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Peijun Sang | Organizer: Yuhang Xu, Shu Yang |
| A0270: P. Sang, D. Kong, S. Yang | |
| Functional principal component analysis under informative sampling | |
| A0274: L. Xiao | |
| Joint model for survival and multivariate sparse functional data for Alzheimer's disease | |
| A0281: G. Li | |
| Analysis of microbiome differential abundance by pooling Tobit models | |
| A0640: Y. Sun | |
| Semiparametric joint modeling for biomarker trajectory before disease onset |
| Session EO159 | Room: 204 |
| Recent advancements in Bayesian modeling | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Xiaojing Wang | Organizer: Xiaojing Wang |
| A1104: X. Wang, Y. Liu | |
| Bayesian Nonparametric Monotone Regression of Dynamic Latent Traits in Item Response Theory Models | |
| A1107: E. Conlon, Z.D. Wei | |
| Parallel computing methods for Bayesian analysis of big data sets | |
| A1113: Y. Li | |
| A uniform shrinkage prior in spatiotemporal Poisson models for count data | |
| A1101: W. Wu, G. Chen | |
| Does the adjustment cost of future resource expansion affect labor cost stickiness? |
| Session EO029 | Room: 207 |
| Statistical inference for high-dimensional data | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Alfonso Landeros | Organizer: Weixin Yao |
| A0265: R. Jiang | |
| Unconditional quantile regression for streaming data sets | |
| A0282: J. Sanchez Gomez | |
| Detecting hub variables in large Gaussian graphical models | |
| A1022: Z. Zeng | |
| Simultaneous quantile regression models: Homogeneity, sparsity, and efficiency | |
| A1036: A. Landeros | |
| The proximal distance principle: Algorithms and applications |
| Session EO225 | Room: 209 |
| Advanced statistical methods for analyzing complex data | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Fengqing Zhang | Organizer: Fengqing Zhang |
| A0183: Y. Wang | |
| A Bayesian regression model with misreported response | |
| A0236: C. Li, S. Sun, Y. Zhu | |
| Bayesian fixed-domain asymptotics for covariance parameters in spatial Gaussian process models | |
| A0394: P. Zhang | |
| Link prediction problems in functional brain networks | |
| A0211: J. Gou | |
| Graphical approaches and reverse graphical approaches in clinical studies with multiple endpoints |
| Session EO155 | Room: 210 |
| Statistical methods for biological data analysis and bioinformatics | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Zeny Feng | Organizer: Zeny Feng |
| A0356: L. Li | |
| Z-residual diagnostics for Bayesian hurdle models | |
| A0491: Y. Li | |
| Statistical methods applied in microbial metagenomics | |
| A0493: C. Feng | |
| Randomized quantile residuals for diagnosing zero-inflated models with applications to microbiome count data | |
| A0741: Z. Feng, A. Cooper, A. Ali, L. Deeth, T. Arciszewski | |
| Optimization of the regularized Dirichlet multinomial regression and its application in compositional data analysis |
| Session EO311 | Room: 212 |
| Advances in big data analysis and dimension asymptotics (virtual) | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Fei Tan | Organizer: Hanxiang Peng, Fei Tan |
| A0759: F. Tan, X. Zhao, H. Peng | |
| The A-optimal subsampling approach to the analysis of count data of massive size | |
| A0655: Y. Zhu | |
| Predictive model degrees of freedom in linear regression | |
| A0763: H. Peng, F. Li, H. Smithson | |
| The A-optimal subsampling for big data penalized spline single index models | |
| A0777: S. Zhang | |
| Subsample size determination with different approaches |
| Session EO020 | Room: 307 |
| Frontiers in nonparametric statistics and functional data analysis | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Xinyi Li | Organizer: Xinyi Li |
| A0473: M. Kim, G. Goh | |
| A sparse empirical Bayes approach to high-dimensional Gaussian process-based varying coefficient models | |
| A0520: G. Wang, Z. Gu, X. Li, L. Wang | |
| Spatially-varying coefficient models with structure identification | |
| A0561: W. Zhang | |
| Regularizing BELIEF for smooth dependency | |
| A0727: E. Cui | |
| Fast multilevel functional principal component analysis |
| Session EO259 | Room: 313 |
| Modern developments in space-time modeling | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Yawen Guan | Organizer: Hsin-Cheng Huang, Whitney Huang |
| Session EO035 | Room: 405 |
| Advancing statistical inference for complex data | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Meimei Liu | Organizer: Meimei Liu |
| Session EO212 | Room: 406 |
| Recent developments in reliability analysis | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Man Ho Ling | Organizer: Man Ho Ling |
| A1048: H.Y. So | |
| Imputations in one-shot devices data using machine learning algorithms | |
| A1039: D. Mitra, A. Ganguly | |
| Reliability analysis of load-sharing systems using a flexible model with piecewise linear functions | |
| A0800: H. Nagatsuka, S. Kaneko | |
| On parameter estimation for generalized inverse Gaussian distribution | |
| A0174: M.H. Ling | |
| Extended gamma process model for accelerated destructive degradation analysis |
| Session EO082 | Room: 408 |
| Statistical demography | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Zehang Li | Organizer: Zehang Li |
| Session EO191 | Room: 411 (Virtual sessions) |
| Recent advances in Bayesian methods and applications | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Dongu Han | Organizer: Taeryon Choi |
| A0899: D. Han, K. Lee, Y. Chung, G. Kobayashi, T. Choi | |
| Semiparametric Bayesian two-stage meta-analysis between ambient temperature and daily confirmed cases of COVID-19 | |
| A0919: H. Kim, A. Kottas | |
| Bayesian nonparametric model of marked Hawkes processes, with application to earthquake occurrences | |
| A0926: G. Kobayashi, S. Sugasawa, Y. Kawakubo, T. Choi, D. Han | |
| Predicting COVID-19 hospitalization using a mixture of Bayesian predictive syntheses | |
| A0972: D. Yang, T. Choi | |
| Robust Bayesian change point detection |
| Session EC301 | Room: 202 |
| High-dimensional statistics | Wednesday 17.7.2024 10:20 - 12:00 |
| Chair: Runmin Wang | Organizer: EcoSta |
| A1037: T. Kenney, H. Gu, S. Organ | |
| Vertex cover matroid variable selection | |
| A1060: Y. Tang, R. Martin | |
| Empirical priors inference in sparse high-dimensional generalized linear models | |
| A1033: H. Gu, T. Kenney, M. Hayes, T. Huang | |
| Poisson principal component analysis and its ensemble approaches for cross-study analyses | |
| A0563: X. Li | |
| Testing for the equality of distributions in high dimension |
| Parallel session C: EcoSta2024 | Wednesday 17.7.2024 | 13:30 - 15:10 |
| Session EO043 | Room: 102 |
| New advances in time series analysis and econometrics | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Kun Chen | Organizer: Kun Chen |
| A0915: H.-H. Huang | |
| Sparse matrix estimation based on greedy algorithms and information criteria | |
| A1004: R. Huang, K. Chen, Z. Tong | |
| Predictive subgroup logistic regression: A new approach in customer churn modeling with unobserved heterogeneity | |
| A1054: X. Tang | |
| Asymptotic and bootstrap inference for change-points in time series | |
| A1041: K. Chen, R. Huang, X. He | |
| A frequency domain functional approach for time series classification with application to epileptic seizure |
| Session EO184 | Room: 103 |
| Recent advances in statistics | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Le Zhou | Organizer: Le Zhou |
| A0189: Y. Chen, S.-C. Lin, Y. Zhou, O. Carmichael, J.-L. Wang, H.-G. Mueller | |
| Gradient synchronization for multivariate functional data, with application to brain connectivity | |
| A0679: L. Xia, M.-Y. Cheng, D. Siegmund, S. Wang | |
| Inference for changing periodicity, smooth trend and covariate effects in nonstationary time series | |
| A0995: A. Yang | |
| Flexible regularized estimating equations: Some new perspectives |
| Session EO145 | Room: 104 |
| New advances in statistical learning | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Di He | Organizer: Boxiang Wang |
| A0346: Z. Wang | |
| Bayesian edge regression: Characterizing observation-specific heterogeneity in estimating undirected graphical models | |
| A0401: J. Zhang, Y. Yang, J. Ding | |
| Additive-effect assisted learning | |
| A0740: J. Fan | |
| Information theoretic learning meets deep neural networks | |
| A0851: C. Xie | |
| Enhancing the power of OOD detection via sample-aware model selection |
| Session EO325 | Room: 105 |
| Agricultural economics in China | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Shangpu Li | Organizer: Shangpu Li |
| Session EO183 | Room: 106 |
| Recent advances in high-dimensional change point inference | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Runmin Wang | Organizer: Runmin Wang |
| A0444: X. Zhang, K.-S. Chan | |
| Adaptive matrix change point detection: Leveraging structured mean shifts | |
| A0853: B. Liu | |
| Change point detection for high-dimensional linear models: A general tail-adaptive approach | |
| A1063: G. Wang | |
| Exact and assumption-lean change-point detection with applications in post-detection inference | |
| A1110: W.Z. Kua, C.Y. Yau | |
| Controlling FDR of change points in structural break time series |
| Session EO030 | Room: 108 |
| Statistical learning on data with sophisticated structures and dependence | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Wen Zhou | Organizer: Wen Zhou |
| A0443: K. Zhang, X.-L. Meng, B. Brown | |
| BELIEF in dependence: Leveraging atomic linearity in data bits for rethinking generalized linear models | |
| A0457: X. Tong, J. Fan, S. Yao, Y. Wu | |
| Neyman-Pearson and equal opportunity: When efficiency meets fairness in classification | |
| A0486: Z. Zhao, X. Xing | |
| On the testing of multiple hypothesis in sliced inverse regression | |
| A0522: Z. Ren | |
| Sparse heteroskedastic PCA in high dimensions |
| Session EO232 | Room: 109 |
| Statistical/Machine learning and applications | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Jingjing Wu | Organizer: Jingjing Wu |
| A0867: S. Ma, Y. Zheng | |
| Analysis of the impact mechanism of talent agglomeration on the high quality development of Chinese urban economy | |
| A0707: J. Ren, R. Huang, J. Liu, H. Deng, B. Li | |
| Exploring the evolution law of intelligent voice technology using text mining | |
| A0999: J. C-Rella, D. Martinez Rego, J. Vilar Fernandez | |
| Reinforcement learning in credit risk management | |
| A0234: S. Tian, Q. Bai, C.W.-S. Chen | |
| The impact of news-based and Twitter-based economic uncertainty on realized volatility |
| Session EO111 | Room: 110 |
| Recent advancements in experimental design and its application | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Fasheng Sun | Organizer: Fasheng Sun |
| Session EO041 | Room: 202 |
| Recent development of dimension reduction and semiparametric regression | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Jing Zeng | Organizer: Jing Zeng |
| Session EO213 | Room: 207 |
| Hierarchical and joint statistical models in health and applications | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Gang Han | Organizer: Gang Han |
| Session EO238 | Room: 209 |
| Fast denoising techniques for complex data structures | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Weixing Song | Organizer: Weixing Song |
| Session EO044 | Room: 210 |
| Spatial statistics | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Pei-Sheng Lin | Organizer: Pei-Sheng Lin |
| A0365: C.-S. Chen, C.-W. Shen | |
| Estimation and selection for spatial zero-inflated count models | |
| A0733: V.Y.-J. Chen | |
| Instrumental variable estimation and inference for spatial autoregressive geographically weighted quantile regression | |
| A0908: H.-Y. Yuan, Y. Zheng, K. Yue, E.W.M. Wong | |
| Association of human mobility and weather conditions with dengue mosquito abundance in three areas in Hong Kong | |
| A0942: F.-C. Lin, P.-S. Lin, J. Zhu, Y. Jiang | |
| Local linear estimation for covariate-dependent coefficients model in disease mapping |
| Session EO193 | Room: 212 |
| Modern semiparametric methods with applications | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Myungjin Kim | Organizer: Myungjin Kim |
| A0289: Y. Chen, M. Kim | |
| Amenity alchemy: Unveiling the dual nature of amenities in shaping regional futures | |
| A0383: D. Lee, S. Chen | |
| Data integration with nonprobability sample: Semiparametric model-assisted approach | |
| A0595: J. Mu | |
| Variable selection for ultra-high-dimensional generalized spatial partial varying coefficient models | |
| A1064: D. Murakami, S. Shirota, M. Kajita, S. Kajita | |
| A fast and flexible space-time varying coefficient model selection |
| Session EO012 | Room: 307 |
| Recent advances in functional data analysis (virtual) | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Eftychia Solea | Organizer: Eftychia Solea |
| A0478: J. Song | |
| Sparse modeling and non-asymptotic bounds via correlation operator of multivariate functional data | |
| A0646: C. Capezza, F. Centofanti, A. Lepore, B. Palumbo | |
| Robust statistical process monitoring of multivariate profiles | |
| A1017: E. Christou, E. Solea, S. Wang, J. Song | |
| Sufficient dimension reduction for conditional quantiles for functional data | |
| A1081: J. Di Iorio | |
| Motif discovery driven forecasting for functional data |
| Session EO015 | Room: 313 |
| Recent advances in nonlinear time series | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Guodong Li | Organizer: Philip Yu |
| A0217: W.-K. Li, Y. Zhuang, D. Li, P. Yu | |
| On buffered moving average models | |
| A0337: Y. Li, K. Chen, C.Y. Yau | |
| Functional threshold autoregressive model | |
| A0503: X. Wang, P. Yu, L. Xin | |
| Uncover networks of R\&D activities by a two-way constrained MAR model | |
| A0433: G. Li | |
| Supervised factor modeling for high-dimensional linear time series |
| Session EO031 | Room: 405 |
| New developments in statistical inference for non-Gaussian data | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Zheng Wei | Organizer: Zheng Wei |
| A0887: Z. Wang | |
| Extending APP for skew normal distributions using Bonferroni method | |
| A1077: S. Gao, B. Choy, Y. Zhang, J. Gao, R. Li | |
| Probabilistic loss reserving prediction via denoising diffusion model | |
| A0879: B. Choy, X. Li | |
| Robust Bayesian A/B testing | |
| A0890: Z. Wei | |
| Bayesian stochastic frontier models under the skew normal settings |
| Session EO229 | Room: 406 |
| Statistical learning with applications | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Shengtong Han | Organizer: Shengtong Han |
| Session EO247 | Room: 408 |
| Sufficient dimension reduction (virtual) | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Kyongwon Kim | Organizer: Kyongwon Kim |
| A0475: G. Kwon | |
| On sparse directional regression | |
| A0523: C. Ryu | |
| On a SAVE and DR for large scale dataset | |
| A0609: A.R. Lee | |
| Multivariate response directional regression: An approach via projective resampling method | |
| A0746: H. Quach, W. Guo, W. Yang | |
| A novel basis expansion for functional sliced inverse regression |
| Session EO202 | Room: 411 (Virtual sessions) |
| Recent development of spatial data and time series analysis | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Takaki Sato | Organizer: Daisuke Kurisu |
| A0177: T. Ito, S. Sugasawa | |
| Grouped GEE for heterogeneous longitudinal data | |
| A0344: M. Toyoda, Y. Uematsu | |
| Powerful multiple test with a fixed sample size | |
| A0530: T. Sato | |
| GMM estimation of spatial autoregressive models with cluster-dependent errors | |
| A0806: T. Takabatake | |
| Likelihood-based analysis of general Gaussian processes having scaling properties |
| Session EC270 | Room: 111 |
| Survival analysis | Wednesday 17.7.2024 13:30 - 15:10 |
| Chair: Matias Quiroz | Organizer: EcoSta |
| A0850: J.-J. Hsieh | |
| Accelerated failure time model under dependent truncated data | |
| A0976: A. Lopez-Cheda, S. Saavedra, M.A. Jacome | |
| A presmoothed estimator for the cure probability: An application to a cardiotoxicity dataset | |
| A0979: B. Pineiro-Lamas, A. Lopez-Cheda, R. Cao | |
| High dimensional single-index mixture cure models in cardio-oncology | |
| A1045: M.A. Jacome Pumar, B.E. Monroy-Castillo, R. Cao | |
| Testing covariate effects in the mixture cure model using distance correlation |
| Parallel session E: EcoSta2024 | Wednesday 17.7.2024 | 16:40 - 18:20 |
| Session EI008 (Special Invited Session) | Room: 106 |
| Recent development based on stochastic processes | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Catherine Liu | Organizer: Catherine Liu |
| A0180: Y. Li | |
| Functional principal component analysis of spatially and temporally indexed point processes | |
| A0152: C. Liu | |
| Jump-size-based Bayesian detection of multiple change-points | |
| A0179: J.Q. Shi, Y. Zhang, X. Wang | |
| Bayesian analysis of nonlinear structured latent factor models using a Gaussian process prior |
| Session EO257 | Room: 102 |
| Structural macroeconometrics | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Roberto Leon-Gonzalez | Organizer: Roberto Leon-Gonzalez |
| Session EO105 | Room: 103 |
| Advancements in latent variable modeling | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Shiyu Wang | Organizer: Yuan Ke, Shiyu Wang |
| A0332: Z. Liu, S. Wang, S. Zhang, T. Qiu, H. Xiao | |
| Dynamic cognitive diagnostic frameworks: A general model for learning | |
| A0381: S. Wang, Y. Ke, C. Cheng | |
| Calibrating item response theory models with sparse data | |
| A0412: S. Yang, J. Wang | |
| Examining the usage of rating scale in subjective creativity assessments through partial credit model | |
| A0459: S. Peng, Y. Cai, D. Tu | |
| Willing and able to fake: A new and flexible item response model for applicant faking |
| Session EO107 | Room: 104 |
| Recent developments in network modeling and applications | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Dongxue Zhang | Organizer: Wei Lan |
| A0464: D. Zhang | |
| High-dimensional-responses-assisted heterogeneous nodal influence analysis | |
| A0468: B. Yu, X. Li, J. Zhou, H. Wang | |
| A Gaussian mixture model for multiple instance learning with partially subsampled instances | |
| A0471: X. Fan, W. Lan, K. Fang | |
| Network varying coefficient model | |
| A0665: B. Liu | |
| Interpret how external shocks affect industrial chain using graph machine learning |
| Session EO196 | Room: 105 |
| Data twins: Efficient data collection and effective data analysis | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Xiaoning Kang | Organizer: Xinwei Deng, Xiaoning Kang |
| A0818: F.K.H. Phoa, J.-W. Huang, Y.-H. Chen, Y.-H. Lin, S.P. Lin | |
| An efficient approach for identifying important biomarkers for biomedical diagnosis | |
| A0840: X. Cai | |
| Change-point detection in generalized extreme value distribution via generalized fiducial inference | |
| A1084: S. Xiong | |
| A discrepancy decomposition model for calibration experiments | |
| A1085: Q. Liang | |
| Risk-adjusted monitoring of online user-generated reviews via user preference learning |
| Session EO187 | Room: 109 |
| Statistical learning methods for complex biomedical data analysis | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Jian Kang | Organizer: Jian Kang |
| Session EO094 | Room: 110 |
| Design and analysis of computer experiments | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Wenlong Li | Organizer: Xu He |
| A0295: W. Li, Y. Tian, M.-Q. Liu | |
| Construction of orthogonal maximin distance designs | |
| A0301: W. Xu | |
| Feature calibration for computer models | |
| A0537: Z. Li | |
| SIGMA: Stochastic differential equations informed Gaussian process model for parameter inference | |
| A0897: Y. Wang | |
| Sequential Latin hypercube design for two-layer computer simulators |
| Session EO089 | Room: 111 |
| Novel statistical models and methods with applications | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Yingying Ma | Organizer: Yingying Ma |
| A0161: Y. Gao, Z. Zhang, X. Zhu, Z. Cai, T. Zou, H. Wang | |
| Penalized sparse covariance regression with high dimensional covariates | |
| A0164: Y. Zhu | |
| A communication efficient boosting method for distributed spectral clustering | |
| A0376: S. Wu, X. Zhu, H. Wang | |
| Subsampling and jackknifing: A convenient solution for large data analysis with limited computational resources | |
| A0894: H. Qi, F. Wang, H. Wang | |
| Statistical analysis of fixed mini-batch gradient descent estimator |
| Session EO171 | Room: 202 |
| Recent advances in statistical process monitoring and change point detection | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Jun Li | Organizer: Jun Li |
| A0971: P. Qiu | |
| Spatiotemporal surveillance of infectious diseases by statistical process control charts | |
| A1083: Y. Xie, A. Kipnis, T. Gong | |
| Higher-criticism for multi-sensor change-point detection | |
| A0755: O.H. Madrid Padilla, L. Cappello | |
| Variance change point detection with credible sets | |
| A1074: W. Ning | |
| Nonparametric Shiryaev-Roberts change-point detection |
| Session EO177 | Room: 204 |
| Advances in random forests and causal inference (virtual) | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Hiroshi Shiraishi | Organizer: Hiroshi Shiraishi |
| A1028: T. Nakamura, H. Shiraishi | |
| Data adaptive random forest kernels via dimension reduction | |
| A1049: X. Lin, H. Shiraishi | |
| An application of random forests to estimate the reporting delay in COVID-19 cases | |
| A0944: H. Shiraishi, T. Nakamura, R. Suzuki | |
| Asymptotic property for generalized random forests |
| Session EO217 | Room: 207 |
| Recent advances in causal inference and its applications | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Yuexia Zhang | Organizer: Yuexia Zhang |
| Session EO317 | Room: 209 |
| Clustering and classification for time series | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Angel Lopez Oriona | Organizer: Angel Lopez Oriona |
| A0241: A. Lopez Oriona | |
| Fuzzy clustering of circular time series based on a new dependence measure with applications to wind data | |
| A0255: S. Aslan, C. Yozgatligil, C. Iyigun | |
| Dynamic clustering of multivariate time series using DTGARCH model and spectral clustering | |
| A0546: T. Chen | |
| Robust linkage methods for functional data clustering | |
| A0616: C. Tang, H.L. Shang, Y. Yang, Y. Yang | |
| Homogeneity pursuit in forecasting high-dimensional functional time series: Is clustering necessary |
| Session EO025 | Room: 210 |
| Design and analysis for order-of-addition experiments | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Fasheng Sun | Organizer: Min-Qian Liu |
| A0407: F. Sun, Q. Zhao, Q. Xiao, A. Mandal | |
| Optimal designs for order-of-addition two-level factorial experiments | |
| A0436: X. Chen | |
| Symmetrical analysis for the order-of-addition experiments | |
| A0736: H. Huang | |
| Design for order-of-addition experiments with two level components | |
| A0572: B. Guo | |
| Minimum aberration designs for order of addition experiments |
| Session EO070 | Room: 212 |
| Recent advances and development in statistical modeling | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Li-Hsien Sun | Organizer: Li-Hsien Sun |
| A0230: I.-T. Yu | |
| Increment degradation model: A Bayesian perspective | |
| A0492: L.-H. Sun, C.-Y. Chiu | |
| Adaptive change point estimation: Interval time series analysis for GBM models | |
| A0507: S.-F. Huang, W.-T. Lai, R.-B. Chen | |
| A modified VAR-deGARCH model for asynchronous multivariate financial time series via variational Bayesian inference | |
| A0633: C. Chang | |
| Estimation of threshold-boundary logistic regression models |
| Session EO165 | Room: 307 |
| Recent development on dependent functional data | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Han Lin Shang | Organizer: Han Lin Shang |
| A0467: Y. Yang, H.L. Shang | |
| Nonstationary functional time series forecasting | |
| A0480: H.L. Shang, C.F. Jimenez Varon, Y. Sun | |
| Forecasting density-valued functional panel data | |
| A0635: Y. Yang, Y. Gao, H.L. Shang, Y. Yang | |
| Eigen-analysis for functional time series | |
| A0738: W. Dai | |
| Enhanced functional data alignment with exogenous variables |
| Session EO074 | Room: 313 |
| Large-scale time series models | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Yubo Tao | Organizer: Degui Li |
| Session EO091 | Room: 405 |
| Recent advances in statistical methods for stochastic processes | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Masayuki Uchida | Organizer: Masayuki Uchida |
| A0328: M. Uchida, Y. Tonaki, Y. Kaino | |
| Estimation for a discretely observed linear parabolic SPDE in two space dimensions based on triple increments | |
| A0347: Y. Shimizu | |
| Approximation and estimation of scale functions for spectrally negative Levy processes | |
| A0474: Y. Koike | |
| Estimation of the number of relevant factors from high-frequency data | |
| A0479: A. Gloter, C. Amorino, H. Halconruy | |
| Locally differentially private drift parameter estimation for iid paths of diffusion processes |
| Session EO081 | Room: 406 |
| Modeling multivariate extremes: Theory and applications | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Pavel Krupskiy | Organizer: Pavel Krupskiy |
| A0368: L. Peng, W. Huang, S. Li | |
| Estimation and inference for extreme continuous treatment effects | |
| A0482: J. Richards, C. Murphy-Barltrop, R. Majumder | |
| A deep geometric approach to modelling multivariate extremes | |
| A0524: P. Zhong, B. Beranger, S. Sisson | |
| Flexible max stable processes for fast and efficient inference | |
| A0559: L. Tafakori | |
| Estimation of max-stable random fields using the periodogram for extreme events |
| Session EO254 | Room: 408 |
| Recent advances in experimental design and analysis | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Qian Xiao | Organizer: Qian Xiao |
| A0366: R. Yuan, Y. Yin, H. Xu, M.-Q. Liu | |
| A construction method for Maximin L1-distance Latin hypercube designs | |
| A0367: Y. Li | |
| Penalized additive Gaussian process for auto-tuning of quantitative and qualitative factors in Black-Box systems | |
| A0579: F. Yang | |
| Uniform designs for experiments with branching and nested factors | |
| A0854: D. Wang | |
| A distance metric based space filling subsampling method for nonparametric models |
| Session EO016 | Room: 411 (Virtual sessions) |
| Extreme value modelling, prediction and risk assessment | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Stefano Rizzelli | Organizer: Stefano Rizzelli |
| A0552: G. Stupfler, A. Daouia, A. Usseglio-Carleve | |
| Inference for extremal regression with dependent heavy-tailed data | |
| A0570: D. Carl, S. Padoan, S. Rizzelli | |
| Asymptotic properties of the maximum likelihood estimator within the block maxima framework | |
| A0883: N. Gnecco, E. Merga Terefe, S. Engelke | |
| Extremal random forests | |
| A0932: S. Padoan, S. Rizzelli | |
| Likelihood-based inference for the peaks-over-threshold method in time series |
| Session EC287 | Room: 108 |
| Computational and methodological statistics | Wednesday 17.7.2024 16:40 - 18:20 |
| Chair: Shan Yu | Organizer: EcoSta |
| A0952: M. Kuroda | |
| Fast computation of the bootstrap method for incomplete data | |
| A0977: R. Okano, M. Imaizumi | |
| Wasserstein k-centers clustering for distributional data | |
| A0290: H. Raubenheimer, R. de Jongh, C. Pretorius, T. de Wet | |
| A multiplier approach for nonparametric estimation of the extreme quantiles of compound frequency distributions | |
| A1119: V. Ficcadenti, R. Mattera, R. Cerqueti | |
| Refining soccer rankings: Balancing scored points, goals for and against with kendall correlations and radar charts |
| Parallel session F: EcoSta2024 | Thursday 18.7.2024 | 08:15 - 09:55 |
| Session EO048 | Room: 102 |
| Macroeconomic policies (virtual) | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Etsuro Shioji | Organizer: Etsuro Shioji |
| A0788: T. Fueki, J. Nakajima | |
| Automation and monetary policy: An empirical investigation | |
| A0796: T. Sekine | |
| How do people tweet against inflation in Japan | |
| A0663: H. Morita | |
| Forecasting GDP growth using stock returns in Japan: A factor-augmented MIDAS approach | |
| A0432: E. Shioji | |
| Responses of households' expected inflation to oil prices and the exchange rate: Evidence from daily data |
| Session EO080 | Room: 103 |
| Bootstrap methods in modern settings | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Miles Lopes | Organizer: Miles Lopes |
| A0298: N. Zou, P. Bertail, L. Peng, D. Politis, H.L. Shang, S. Volgushev | |
| When does massive data bootstrap work | |
| A0314: A. Giessing | |
| New Gaussian and bootstrap approximations for suprema of empirical processes | |
| A0320: R. Masini | |
| Yurinskii's coupling for martingales | |
| A0336: Q. Zhao, E. Candes | |
| A resized parametric bootstrap method for inference of a high-dimensional generalized linear model |
| Session EO250 | Room: 104 |
| Recent advances in factor models (virtual) | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Sung Hoon Choi | Organizer: Sung Hoon Choi |
| Session EO207 | Room: 105 |
| Applying doubly robust methods to improve finite population inferences | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Lingxiao Wang | Organizer: Lingxiao Wang |
| Session EO069 | Room: 106 |
| High-dimensional inference and network analysis | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Daoji Li | Organizer: Daoji Li |
| A0232: L. Gao, J. Lv, Y. Fan | |
| Robust knockoffs inference via coupling | |
| A0242: Z. Liang | |
| Integrative conformal p-values for out-of-distribution testing with labeled outliers | |
| A1099: W. Wu | |
| On partial envelope approach for modeling spatial-temporally dependent data | |
| A1117: Y. Wei, S. Riley, A. Connor, W.-Y. Tse | |
| A comparison of methods for externally validating the Kidney Donor Risk Index in the UK kidney transplant population |
| Session EO090 | Room: 108 |
| Statistical learning from complex data | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Fengrong Wei | Organizer: Hongxiao Zhu |
| A0240: F. Wei, W. Tian | |
| Holding-linked network in mutual fund and the predictability of performance | |
| A0515: R. Lu | |
| Bayesian single and multiple index models with additive regression trees | |
| A0594: J. Lee, H. Zhu | |
| Learning from heterogeneous data with stick-breaking variational autoencoder | |
| A0680: X. Wu, H. Zhu | |
| Discovering dependence structure of transcription factors based on a nonhomogeneous Poisson process model |
| Session EO084 | Room: 109 |
| Innovative statistical learning methods for complex data | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Yeying Zhu | Organizer: Yeying Zhu |
| A0187: Q. Wang, Y. Zhao, T. Zhang | |
| Jackknife empirical likelihood for infinite-order U-statistics with applications to ensemble predictions | |
| A0627: Y. Qin, M. Zhu, L. Zheng, Y. Wu, W. Li | |
| Estimation of multiple large covariance matrices and its application to high-dimensional quadratic discriminant analysis | |
| A0657: X. Cai, Q. Wang, Y. Zhu | |
| Mediation analysis with latent factors using simultaneous group-wise and parameter-wise penalization | |
| A0873: L. Diao | |
| Polya trees for survival data |
| Session EO075 | Room: 110 |
| Space filling designs and factorial designs | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Wei Zheng | Organizer: Wei Zheng |
| A0358: X. Zhang | |
| Construction of maximin distance Latin hypercube designs via good lattice point sets | |
| A0410: C. Shi, B. Tang | |
| On construction of nonregular two-level factorial designs with maximum generalized resolutions | |
| A0497: Z. Zhou | |
| Fast approximation of Shapley values via design methods | |
| A0540: X. Kong | |
| Space filling designs on Riemannian manifolds |
| Session EO208 | Room: 111 |
| Conformal prediction and inference | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Yuan Zhang | Organizer: Yuan Zhang |
| A0173: Y. Jin, E. Candes | |
| Model-free selective inference: Selecting trusted decisions from black boxes | |
| A0202: Y. Gui, R. Foygel Barber, C. Ma | |
| Conformalized matrix completion | |
| A0489: L. Guan | |
| A conformal test of linear models via permutation-augmented regressions | |
| A0674: F. Wang, S. Kurtek, Y. Zhang | |
| Conformal prediction for fragmented functional data |
| Session EO112 | Room: 202 |
| Recent advances in statistical methods and theory | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Mengyu Xu | Organizer: Mengyu Xu |
| A0253: T. Zhang | |
| Asymptotics of sample tail autocorrelations for tail dependent time series: Phase transition and visualization | |
| A0661: W. Li, C. Chang, S. Kundu, Q. Long | |
| Accounting for network noise in graph-guided Bayesian modeling of structured high-dimensional data | |
| A0684: Y. Zhao | |
| Whittle estimation based on the extremal spectral density of a heavy-tailed random field | |
| A0742: J. Chung, Q. Zhang, C. Park | |
| Joint graphical lasso with regularized aggregation for high-dimensional time series with long-memory |
| Session EO188 | Room: 204 |
| Advances in Markov chain Monte Carlo | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Qian Qin | Organizer: Qian Qin |
| A0682: H. Li, Q. Qin | |
| Multivariate strong invariance principle and uncertainty assessment for time in-homogeneous cyclic MCMC samplers | |
| A0364: Q. Zhou, A. Smith, G. Li | |
| Importance tempering of Markov chain Monte Carlo methods | |
| A0389: N. Ju, Q. Qin, G. Wang | |
| Spectral gap bounds for reversible hybrid Gibbs chains | |
| A0361: G. Wang, W. Yuan | |
| MCMC when you do not want to evaluate the target distribution |
| Session EO244 | Room: 207 |
| Design and analysis for evaluating causal, moderation, and mediation effects | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Xu Qin | Organizer: Xu Qin, Yan Zhuang |
| A0831: W. Li, S. Konstantopoulos, Z. Shen | |
| Optimal sample size planning for longitudinal multisite experiments to investigate the main and moderator effects | |
| A0833: G. Hong | |
| Stochastic noncompliance and endogenous confounding in evaluating a multi-phase treatment: Multi-site IV as a solution | |
| A0837: X. Qin | |
| A causal investigation of heterogeneity in mediation mechanisms in multisite randomized trials | |
| A0856: C. Liu, X. Qin, J. Wang | |
| Heterogeneous causal mediation analysis with Bayesian additive regression trees |
| Session EO221 | Room: 209 |
| Statistical innovations for complex data analysis in biomedical research | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Kaiqiong Zhao | Organizer: Kaiqiong Zhao |
| Session EO078 | Room: 210 |
| Statistical inference on complex data | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Zhao Ren | Organizer: Zhao Ren |
| A0811: S. Iyengar | |
| Early indicators of degradation of materials with applications to batteries | |
| A0555: Y. Fang | |
| COVID-19 surveillance via adaptive Fisher's method using weakly geometric grid for combining p-values | |
| A0667: X. Yu | |
| A unifying dependent combination framework with applications to association tests | |
| A0167: W. Zhou, X. Tang, L. Zhang, L. Wang | |
| Innovative unsupervised approach for simultaneous subgroup recovery and group-specific feature identification |
| Session EO053 | Room: 212 |
| Statistical and/or pharmacometric considerations in drug development | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Yisheng Li | Organizer: Yisheng Li |
| Session EO049 | Room: 307 |
| Topics in functional and object data analysis | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Kuang-Yao Lee | Organizer: Kuang-Yao Lee |
| A1082: B. Li | |
| Nonlinear global Frechet regression for random objects via weak conditional expectation | |
| A0676: Z. Lin, Y. Lin | |
| Binary regression and classification with covariates in metric spaces | |
| A1030: C. Zhu, H.-G. Mueller | |
| Geodesic optimal transport regression | |
| A1079: K.-Y. Lee, L. Li | |
| Functional structural equation models |
| Session EO246 | Room: 313 |
| New statistical methods for spatial transcriptomics | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Yunshan Duan | Organizer: Sihai Dave Zhao |
| Session EO110 | Room: 405 |
| Statistics advances in change points, bayesian modeling and prediction | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Xin Wang | Organizer: Xin Wang |
| Session EO139 | Room: 406 |
| Advanced topics in statistics and data science | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Shufei Ge | Organizer: Shufei Ge |
| A0246: H. Wang | |
| Nonlinear prediction of functional time series | |
| A0423: X. Fan | |
| Federated event predictions with divergence-guided global aggregation | |
| A0499: Z. Zhou, L. Zhao | |
| A parsimonious joint model of survival outcomes and time-varying biomarkers | |
| A0567: S. Ge | |
| A flexible distribution-guided tool in topology data analysis |
| Session EO024 | Room: 408 |
| New developments in microbiome research | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Gen Li | Organizer: Gen Li |
| Session EO142 | Room: 411 (Virtual sessions) |
| Statistical methods for analyzing high-throughput data | Thursday 18.7.2024 08:15 - 09:55 |
| Chair: Elif Acar | Organizer: Elif Acar |
| A0622: Y. Yilmaz, B. Ryan | |
| Mediation analysis to infer direct genetic effects on disease risks | |
| A0731: O. Espin-Garcia | |
| Leveraging genetic correlation for multi-trait polygenic scores construction via L1 penalized regression | |
| A0997: E. Acar | |
| Automated statistical methods for high-throughput phenotyping experiments | |
| A1001: K. McGregor | |
| Bayesian dimension reduction in microbiome platforms |
| Parallel session G: EcoSta2024 | Thursday 18.7.2024 | 10:25 - 12:30 |
| Session EI007 (Special Invited Session) | Room: 106 |
| New challenges in high-dimensional data analysis | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Binyan Jiang | Organizer: Qing Mai |
| A0208: S. Ma | |
| Modeling emotional expressions for multiple cancers via a linguistic analysis of an online health community | |
| A0934: L. Zhou, D. Cook, H. Zou | |
| Enveloped Huber regression | |
| A1010: J. Zhao | |
| Residual importance weighted transfer learning For high-dimensional linear regression |
| Session EO068 | Room: 102 |
| Statistics and data science for digital finance and tokenomics | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Stephen Chan | Organizer: Stephen Chan, Jeffrey Chu |
| A0698: J. Chu | |
| Network transitions in the cryptocurrency market: The impact of regional conflicts | |
| A0732: M. Yuan | |
| Detecting illicit activity in digital cryptocurrency networks | |
| A0845: S. Chan, J. Chu, Y. Zhang | |
| Empirical analysis of the metaverse non-fungible tokens | |
| A0847: Y. Zhang, S. Chan, J. Chu | |
| Empirical analysis of illicit transactions in blockchain networks | |
| A1015: Y. Chen | |
| Effective multidimensional persistence for Ethereum network representation learning |
| Session EO039 | Room: 103 |
| Spatial panel data models | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Zhenlin Yang | Organizer: Zhenlin Yang |
| A0329: X. Meng | |
| Threshold spatial panel data models with fixed effects | |
| A0338: L. Li | |
| Dynamic spatial panel data models with interactive fixed effects | |
| A0339: C. Yahui, H. Xiaoyi, Z. Jiajun, J. Fei | |
| Efficient and sequential estimation of high-order dynamic spatial panels with time-varying strongly dominant units | |
| A0342: J. Guo, X. Qu | |
| Learning from neighbors: Peer effects in Chinese household financial investments | |
| A0783: Z. Zhang | |
| Firm to firm supply network, urban agglomeration and firms' structure change evidence from structural model |
| Session EO209 | Room: 104 |
| Frontiers of Bayesian methods for complex data | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Fan Bu | Organizer: Alejandra Avalos Pacheco |
| A0484: F. Song, K.Y. Yip, Y. Wei | |
| Regression analysis for single-cell RNA-seq data | |
| A0517: F. Pavone | |
| Phylogenetic latent position model for populations of networks | |
| A0573: F. Fazeliasl, M.M. Zhang | |
| A Bayesian non-parametric approach: Integrating VAEs and GANs using Wasserstein and MMD | |
| A0649: F. Bu | |
| Inferring HIV transmission patterns from viral deep-sequence data via latent spatial Poisson processes |
| Session EO189 | Room: 105 |
| Reliability and precision in modern biomedical research | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Andrew Chen | Organizer: Andrew Chen |
| A0857: B. Caffo | |
| Reliability in functional brain measurement | |
| A0248: T. Xu | |
| Challenges in measuring individual differences and reliability of brain function | |
| A0797: P. Reiss, M. Xu, I. Cribben | |
| Distance-based reliability | |
| A0181: H. Zheng, S. Li, H. Li | |
| Transfer learning methods to get more reliable estimates of effects and predictions | |
| A0583: C. Chen, S. Das, M. Tisdall, F. Hu, A. Chen, P. Yushkevich, D. Wolk, R. Shinohara | |
| Subject-level segmentation accuracy weights for volumetric studies involving label fusion |
| Session EO124 | Room: 108 |
| Statistical learning and inference for large-scale complex data | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Xiufan Yu | Organizer: Xiufan Yu |
| A0379: L. Xie, Y. Yang | |
| Data-driven robust change detection using Wasserstein ambiguity sets | |
| A0753: F. Xue, B. Zhao | |
| High-dimensional statistical inference for linkage disequilibrium score regression and its cross-ancestry extensions | |
| A0809: H. Ren | |
| ByMI Byzantine machine identification with false discovery rate control | |
| A0843: D. Yang, J.J. Cai, H. Shen, W. Zhu, L. Zhao, R. Chen | |
| Network regression and supervised centrality estimation |
| Session EO147 | Room: 109 |
| High-dimensional statistics and random matrix theory | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Zhaoyuan Li | Organizer: Nina Doernemann, Zhaoyuan Li |
| A0363: N. Doernemann, M. Lopes | |
| Tracy-Widom, Gaussian, and Bootstrap: Approximations for leading eigenvalues in high-dimensional PCA | |
| A0504: W. Yuan, J. Yao | |
| On eigenvalue distributions of large auto-covariance matrices | |
| A0805: C.J.L. Louart | |
| Concentration of the measure as an hypothesis for theoretical machine learning | |
| A0541: H. Shi, M. Drton, F. Han | |
| High-dimensional consistent independence testing with maxima of rank correlations | |
| A0838: J. Wang, Z. Bao, X. Ding, K. Wang | |
| Statistical inference for principal components of spiked covariance matrices |
| Session EO186 | Room: 110 |
| Biostatistics, bioinformatics, and causal inference (virtual) | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Li-Pang Chen | Organizer: Li-Pang Chen |
| A0697: L.-P. Chen | |
| Length-biased and partly interval-censored survival data analysis with measurement error in covariates | |
| A0749: Q. Zhang | |
| Bayesian model for disease-specific gene detection in high-dimensional spatially resolved transcriptomics | |
| A0750: A.-S. Tai | |
| Robust and flexible high-dimensional causal mediation model for DNA methylation studies | |
| A0771: J.C. Wu, L.-P. Chen | |
| Ultrahigh-dimensional discriminant analysis and its application to gene expression data | |
| A0774: S.H. Chiou, Y. Chen, C.-F. Tang, M. Chen | |
| Weighted least-squares estimation for semiparametric multivariate accelerated failure time model with regularization |
| Session EO220 | Room: 111 |
| Measurement error and survival data models | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Liqun Wang | Organizer: Liqun Wang |
| A1087: H. Cui | |
| New procedure for controlling false discovery rate in Cox model | |
| A0951: X. Lu, S. Saghatchi, J. Wu | |
| Variable selection for the generalized odds rate non-mixture cure model with current status data | |
| A0770: W. Song | |
| Extrapolation estimation for nonparametric regression with measurement error | |
| A0658: J. Wu | |
| A robust minimum distance estimation of Cox PH models | |
| A0672: L. Wang | |
| Instrumental variable method in regularized regression with mismeasured predictors |
| Session EO120 | Room: 202 |
| High-dimensional genetic and genomic data | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Linxi Liu | Organizer: Linxi Liu |
| Session EO255 | Room: 204 |
| Progress in analyzing censored event times: A contemporary perspective | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Wenyu Gao | Organizer: Wenyu Gao |
| A0656: X. He, C. Chen | |
| Semiparametric analysis of multivariate panel count data with informative observation processes | |
| A0629: I. Kim | |
| Semiparametric Bayesian kernel survival model using multilevel learning | |
| A0198: G. Fang | |
| Multivariate degradation modeling with inverse Gaussian processes | |
| A0199: Y. Wang | |
| Variational inference for spatial correlated failure time data under Bayesian framework | |
| A0204: Y. Pan, X. Ning, Y. Sun, P. Gilbert | |
| Regression analysis of semiparametric Cox-Aalen transformation models with partly interval-censored data |
| Session EO017 | Room: 209 |
| New statistical methods for complex data | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Tianxi Li | Organizer: Tianxi Li, Xuehu Zhu |
| Session EO192 | Room: 210 |
| Statistical inference for complex data | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Robert Lunde | Organizer: Robert Lunde, Xiwei Tang |
| A0360: I. Kim, L. Wasserman, S. Balakrishnan, M. Neykov | |
| Semi-supervised U-statistics | |
| A0668: J. Cape | |
| On varimax asymptotics in network models and spectral methods for dimensionality reduction | |
| A0747: C.M. Madrid Padilla, O. Hernan Madrid, D. Wang | |
| Temporal spatial model via trend filtering | |
| A1108: H. Zhou | |
| Dynamic subgroup analysis on heterogeneous regression model | |
| A1109: J. Wang, R.K.W. Wong, X. Mao, K.C.G. Chan | |
| Matrix completion with model-free weighting |
| Session EO095 | Room: 212 |
| Random fields and their statistical applications | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Dan Cheng | Organizer: Dan Cheng |
| Session EO106 | Room: 307 |
| Recent advances in statistical modeling for neuroimaging data | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Shuo Chen | Organizer: Shuo Chen |
| A0228: X. Luo, Y. Zhao, B. Caffo, M. Lindquist, M. Sobel | |
| Causal mediation analysis for multilevel and functional data | |
| A0424: J.Y. Park, R. Pan, Y. He | |
| Improving statistical power of multi-modal associations via de-variation | |
| A0625: J. Kang | |
| Bayesian inference on brain-computer interfaces via GLASS | |
| A0914: S. Chen, H. Lee | |
| Machine learning to the mean and its correction: An application to imaging-based brain age prediction | |
| A0983: L. Lin | |
| Advancing statistical analyses for living systematic reviews |
| Session EO027 | Room: 313 |
| Research frontiers on time series and multivariate data | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Ting Zhang | Organizer: Ting Zhang |
| A0582: M. Xu, L. Chen, J. Li | |
| Inference for quantile change points in high-dimensional time series | |
| A0664: S. Bai, H. Tang, S. Deng | |
| Clustering multivariate extremes | |
| A0762: B. Wang | |
| High-dimensional clustering via latent semiparametric mixture models | |
| A0764: H. Xiao | |
| Matrix denoising and completion based on Kronecker product approximation | |
| A0785: D. Li | |
| Revisiting Poisson autoregressive models: Structure and statistical inference |
| Session EO154 | Room: 405 |
| Statistical learning and nonparametric methods: Theory and practice | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Guannan Wang | Organizer: Guannan Wang |
| A0254: S. Wang, Y. Huang, R. Li | |
| Inference for quantile mediation effects in the presence of complex confounding via deep neural networks | |
| A0462: X. Song | |
| Nonparametric biomarker based treatment selection with reproducibility data | |
| A0528: Y. Sun, Y. Li, J. Kang | |
| Penalized deep partially linear cox models with application to CT scans of lung cancer patients | |
| A0592: L. Liu, G. Wang, S. Safo | |
| Sparse functional linear discriminant analysis for high-dimensional predictors | |
| A0760: S. Safo | |
| DeepIDA-GRU: A deep learning pipeline for integrative discriminant analysis of cross-sectional and longitudinal |
| Session EO137 | Room: 406 |
| Recent advances in dimension reduction | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Jun Song | Organizer: Jun Song, Wenbo Wu |
| Session EO079 | Room: 408 |
| Advancement in statistical genetics and genomics study | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Xinyi Li | Organizer: Xinyi Li |
| A0545: T. Yang | |
| Advancing graph neural networks for disease classification and feature selection in high-dimensional data | |
| A0621: G. Li | |
| Pseudotime analysis for time-series single-cell sequencing and imaging data | |
| A0593: T. Wang, I. Ionita-Laza, Y. Wei | |
| A unified quantile framework reveals nonlinear heterogeneous transcriptome-wide associations | |
| A0660: N. Awaya, L. Ma | |
| Additive tree flows for density estimation and two-sample comparison | |
| A1061: Z. Khan, S. Aldahmani, A. Ali, H. Du | |
| Double weighting scheme for k-nearest neighbors for binary classification of high-dimensional gene expression data |
| Session EO052 | Room: 411 (Virtual sessions) |
| Advances in macro- and financial econometrics | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Toshiaki Watanabe | Organizer: Toshiaki Watanabe |
| A0269: J. Nakajima | |
| Estimating trend inflation in a regime-switching Phillips curve | |
| A0393: T. Ishihara | |
| Multivariate realized stochastic volatility model using time varying coefficient characteristic factor regression | |
| A0604: D. Hiraki, S. Chib, Y. Omori | |
| Stochastic volatility in mean: Efficient analysis by a generalized mixture sampler | |
| A0564: M. Ubukata | |
| Cross-sectional analysis of stock returns using option-implied tail risk | |
| A0569: M. So, S.H. Chan, A. Chu | |
| Dynamic Bayesian networks with conditional dynamics in edge addition and deletion |
| Session EC281 | Room: 207 |
| Causal inference | Thursday 18.7.2024 10:25 - 12:30 |
| Chair: Cy Sin | Organizer: EcoSta |
| A0751: B. Lu | |
| Individual treatment rule estimation with M-learning | |
| A0947: R. Liu | |
| Double robust Bayesian inference on average treatment effects | |
| A1031: E. Chung | |
| Randomization inference on policy assignments | |
| A1043: K. Kim, E. Kennedy, J. Zubizarreta | |
| Doubly robust counterfactual classification | |
| A1111: L.L. Hui, K.W. Chan | |
| Rematching estimators for average treatment effects |
| Parallel session H: EcoSta2024 | Thursday 18.7.2024 | 14:00 - 15:40 |
| Session EI006 (Special Invited Session) | Room: 106 |
| Recent advances in econometrics | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Massimiliano Caporin | Organizer: Massimiliano Caporin |
| A0156: T. Proietti | |
| Ups and (draw)downs | |
| A0157: P. Poncela, E. Senra, J. Bogalo | |
| Understanding fluctuations through multivariate circulant singular spectrum analysis | |
| A0277: Y. Song, J. Maheu, X. Vu | |
| Variational inference for a Bayesian nonparametric model with structural breaks |
| Session EO125 | Room: 102 |
| Advances in high-dimensional econometrics | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Manabu Asai | Organizer: Manabu Asai |
| A0196: K. Shimizu | |
| Scalable estimation of multinomial response models with uncertain consideration sets | |
| A0299: B. Poignard, Y. Terada | |
| Sparse factor models of high dimension | |
| A0565: M. Asai, B. Poignard | |
| High-dimensional sparse factor multivariate stochastic volatility models | |
| A0693: A. Shinkyu | |
| Testing heteroskedasticity in high-dimensional linear regression |
| Session EO226 | Room: 103 |
| Recent advances in large-scale data analysis | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Yaowu Liu | Organizer: Yaowu Liu |
| A0562: X. Li, S. Yu, Y. Wang, G. Wang, L. Wang, M.-J. Lai | |
| Nonparametric learning for 3D point cloud data | |
| A0599: W. Xiong | |
| A robust integrated mean variance correlation and its use in high dimensional data analysis | |
| A0686: S. Xie | |
| Identifying temporal pathways using biomarkers in the presence of latent non-Gaussian components | |
| A0756: S. Yang | |
| A new regularization method for high-dimensional portfolio selection |
| Session EO085 | Room: 104 |
| Recent advances in time series and panel data econometrics | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Tingting Cheng | Organizer: Tingting Cheng |
| A0374: Y. Yan, J. Gao, B. Peng | |
| Time-varying vector error-correction models: Estimation and inference | |
| A0373: B. Wu | |
| Time-varying generalized network autoregressive models | |
| A0377: F. Liu, J. Gao, B. Peng, Y. Yang | |
| A localized neural network with dependent data: Estimation and inference | |
| A0371: T. Cheng | |
| GMM estimation for high-dimensional panel data models |
| Session EO211 | Room: 105 |
| Recent developments in point processes | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Shizhe Chen | Organizer: Shizhe Chen |
| A0580: Y. Guan | |
| Bias-correction and test for mark-point dependence with replicated marked point processes | |
| A0691: F. Zhou | |
| Is score matching suitable for estimating point processes | |
| A0794: J. Zhuang | |
| Extend the ETAS model step-by-step | |
| A0814: S. Chen, S. Chen, Z. Zhang | |
| Simultaneous estimation and clustering of additive shape invariant models for neural data |
| Session EO251 | Room: 108 |
| Recent advances in statistical learning | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Guo Yu | Organizer: Guo Yu |
| Session EO243 | Room: 109 |
| Recent advances in deep learning: Theory, algorithms and applications | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Puyu Wang | Organizer: Puyu Wang |
| Session EO129 | Room: 110 |
| Recent advances in design theories of experiments | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Qi Zhou | Organizer: Jian-Feng Yang |
| Session EO173 | Room: 111 |
| Statistical modeling and computing methods for complex data | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Victor Hugo Lachos Davila | Organizer: Victor Hugo Lachos Davila |
| A0184: T.-I. Lin, W.-L. Wang, I.-A. Chen | |
| A robust factor analysis model utilizing the canonical fundamental skew-t distribution | |
| A0185: W.-L. Wang | |
| Multivariate contaminated normal censored regression model: Properties and maximum likelihood inference | |
| A0258: J. Luis Bazan, A. de la Cruz Huayanay | |
| Exploring metric performance for binary classification in unbalanced data: A comparative study | |
| A0260: V.H. Lachos Davila, S.D. Tomarchio, S. Ingrassia, A. Punzo | |
| On the matrix-variate normal distribution for interval-censored and missing data | |
| A0218: C.E. Galarza Morales, F. Schumacher, K.A. Loor Valeriano, L. Avila Matos | |
| Censored autoregressive regression models with Student-t innovations |
| Session EO067 | Room: 202 |
| Statistical methodologies for neuroimaging data | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Yi Zhao | Organizer: Yi Zhao |
| Session EO234 | Room: 204 |
| Bayesian analysis with different real-world applications | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Chong Zhong | Organizer: Chong Zhong |
| A0315: J. Zhuo, Z. Cai, X. Han | |
| Bayesian group lasso for spatial autoregressive model with convex combinations of different spatial weights | |
| A0670: Y. Yan | |
| Bayesian integrative region segmentation in spatially resolved transcriptomic studies | |
| A0729: J. Zhang, A. Dassios | |
| Posterior sampling from truncated Ferguson-Klass representation of normalized completely random measure mixtures | |
| A0722: C. Zhong, J. Yang, J. Shen, C. Liu, Z. Li | |
| On posterior mixing under unidentified nonparametric models |
| Session EO215 | Room: 207 |
| Recent advances in precision medicine | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Xinzhou Guo | Organizer: Xinzhou Guo |
| Session EO218 | Room: 209 |
| Statistical methods for complex data | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Archer Yang | Organizer: Archer Yang, Yue Zhao |
| A0866: P. Shang, H. Chen, L. Kong | |
| Safe feature identification rule for fused Lasso by an extra dual variable | |
| A0644: J. Zhou | |
| Extreme marginal quantile treatment effect for high dimensional data | |
| A0968: Y. Zhao | |
| Inference on derivatives of high dimensional regression function with deep neural network | |
| A1034: X. Bing | |
| Linear discriminant regularized regression |
| Session EO203 | Room: 210 |
| Recent advances in statistical inference and complex data analysis | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Yaqing Chen | Organizer: Yaqing Chen |
| A0293: X. Zhang, J. Yan, Z. Li | |
| A distance and kernel-based framework for global and local two-sample conditional distribution testing | |
| A0331: X. Shao, F. Jiang, C. Zhu | |
| Statistical inference for non-Euclidean valued time series | |
| A0340: W. Pan | |
| Region-based functional genome-wide association detection for imaging response | |
| A0354: Y. Yang, Z. Chen, F. Yao | |
| Dynamic matrix recovery |
| Session EO258 | Room: 212 |
| New developments of causal inferences and its applications | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Jinzhu Jia | Organizer: Jinzhu Jia |
| A0710: J. Jia | |
| Nonlinear Mendelian randomization | |
| A0758: W. Ma, L. Zhang | |
| Interaction tests with covariate-adaptive randomization | |
| A0916: Y. Wang, L. Liu | |
| Root-n consistent semiparametric learning with high-dimensional nuisance functions under minimal sparsity | |
| A0990: Z. Liu | |
| Robust Mendelian randomization coupled with Alphafold2 for drug target discovery |
| Session EO181 | Room: 307 |
| Functional data analysis and its applications | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Eliana Christou | Organizer: Eliana Christou |
| A0548: H. Wang, X. Wang | |
| Empirical likelihood inference for functional mean models with application to human cognitive impairment | |
| A0904: S. Wang, E. Christou, E. Solea, J. Song | |
| Dimension reduction for the conditional quantiles of functional data with categorical predictors | |
| A0901: M. Cremona, L. Doroshenko, F. Severino | |
| Functional motif discovery in stock market prices | |
| A0911: E. Solea, E. Christou, J. Song | |
| Robust inverse regression for multivariate elliptical functional data |
| Session EO163 | Room: 313 |
| Advances in complex time series | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Wai-keung Li | Organizer: Wai-keung Li |
| A0359: B. Su, K. Zhu | |
| Inference for the panel ARMA-GARCH model when both N and T are large | |
| A0483: S.H. Chan, A. Chu, M. So | |
| Multi-view dynamic social network modeling | |
| A0574: Y. Cai, F. Huang, K. Lu, Z. Qin, Y. Fang, G. Tian, G. Li | |
| Encoding recurrence into transformers | |
| A0725: X. Wang | |
| Semi-strong double-autoregressive models: Structure and estimation |
| Session EO201 | Room: 405 |
| Stochastic models in statistics | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Soudeep Deb | Organizer: Soudeep Deb |
| A0318: R. Roy | |
| Within game forecasting in T20 cricket, a time series classification approach using parallelism | |
| A0319: A. Ghosh, R. Hore | |
| Robust and efficient parameter estimation for discretely observed stochastic processes | |
| A0605: S. Mukherjee | |
| Limited theorems and phase transitions in tensor Curie-Weiss Ising and Potts models | |
| A0994: Y. Goto, K. Fujimori | |
| A test for counting sequences of integer-valued autoregressive models |
| Session EO066 | Room: 406 |
| New advances in statistical estimation, testing and classification | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Ke Yang | Organizer: Tiejun Tong |
| A0292: Y. Wang | |
| Sparse positive-definite estimation for covariance matrices with repeated measurements | |
| A0162: L. Wang | |
| Hierarchical Neyman-Pearson classification for prioritizing severe disease categories in COVID-19 patient data | |
| A0378: S. Yao | |
| A cross-validation approach for distribution-free two-sample testing with high-dimensional data | |
| A0201: K. Yang, E. Lin, W. Xu, L. Zhu, T. Tong | |
| An intrinsic measure for quantifying the heterogeneity in meta-analysis |
| Session EO102 | Room: 408 |
| At the intersection of statistical learning and machine learning | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Yichen Cheng | Organizer: Yichen Cheng |
| Session EO240 | Room: 411 (Virtual sessions) |
| Recent advances in manifold-related statistical inference | Thursday 18.7.2024 14:00 - 15:40 |
| Chair: Rong Tang | Organizer: Rong Tang |
| A0538: Z. Yao | |
| Random fixed boundary flows: A twin sister of principal flow | |
| A0384: R. Yao | |
| Mean-field variational inference via Wasserstein gradient flow | |
| A0272: V. Divol | |
| Wasserstein convergence of persistence diagrams on generic manifolds | |
| A0275: M.H. Cho | |
| Logistic regression models for elastic shape of curves |
| Parallel session I: EcoSta2024 | Thursday 18.7.2024 | 16:10 - 18:15 |
| Session EV268 | Room: 411 (Virtual sessions) |
| Methodological statistics and econometrics | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Stefano Rizzelli | Organizer: EcoSta |
| A0288: B. Kozyrev | |
| Forecast combination and interpretability using random subspace | |
| A0931: A. Srakar | |
| Spectral CLTs for large language and large multimodal models | |
| A0978: S. Maggio, S. De Iaco | |
| Assessing the probability of museum opening choices and its spatial distribution through multilevel logit kriging |
| Session EO092 | Room: 102 |
| Contributions in theoretical and applied econometrics | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Massimiliano Caporin | Organizer: Massimiliano Caporin |
| A0513: R. Yang | |
| Responsible investing: ESG risk budgeting | |
| A0402: Y. Bai | |
| Nonparametric estimation and forecasting of time-varying parameter models | |
| A0403: Y. Mao | |
| Assessing nonlinear impact of ESG on company performance | |
| A1007: T. Pal, G. Storti | |
| Estimating the natural rate of interest in the US: An accelerating score-driven state space model | |
| A0226: M. Caporin, G. Bonaccolto, J. Shahzad | |
| Quantile spillover indexes: Simulation-based evidence, confidence intervals and a decomposition |
| Session EO058 | Room: 103 |
| New advances in panel data models | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Alexandra Soberon | Organizer: Alexandra Soberon |
| A0239: S. Wei | |
| Estimating latent-variable panel data models using parameter-expanded SEM methods | |
| A0252: L.A. Arteaga Molina, J.M. Rodriguez-Poo | |
| Empirical likelihood based testing device for a semiparametric panel data model with cross-sectional dependence | |
| A0283: J.M. Rodriguez-Poo, A. Soberon, S. Sperlich | |
| Estimation and inference of panel data models with a generalized factor structure | |
| A0291: A. Soberon, D. Henderson, C. Parmeter | |
| Estimation and testing for varying coefficient multidimensional panel data models: A differencing approach | |
| A0350: G. Keilbar, L. Chen, L. Su, W. Wang | |
| Tests for many treatment effects in regression discontinuity panel data models |
| A0296: R. Caballero-Aguila, J. Hu, J. Linares-Perez | |
| Signal estimation from quantized measurements with random matrices, time-correlated noises and miscellaneous attacks | |
| A0510: R.M. Fernandez-Alcala, J.D. Jimenez-Lopez, J. Navarro-Moreno, J.C. Ruiz-Molina | |
| Centralized fusion prediction in hypercomplex systems with random packet dropouts under properness conditions | |
| A0775: H. Zhang | |
| Event-triggered state estimation for time-varying systems under coder-decoder mechanism | |
| A0789: H. Yu, P. Yue, J. Hu, L. Xu | |
| Distributed fusion filtering for multi-sensor multi-rate systems with stochastic nonlinearities and Packet disorders | |
| A0787: J. Hu, B. Lei, N. Lin, Z. Wu | |
| Dynamic-data-encryption-based distributed state estimation for nonlinear complex networks against DoS attacks |
| Session EO166 | Room: 105 |
| Big data computation and applications | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Feng Li | Organizer: Feng Li |
| A0566: X. Shen | |
| Modeling the genetic architecture of human complex traits based on genome-wide association summary statistics | |
| A0500: S. Wang | |
| Distributed sparse regression for high dimensional financial big data based on gradient hard thresholding pursuit | |
| A0706: Z. Xiong, Y. Dong, J. Zhou, X. Zhu, H. Wang | |
| Understanding the impact of emotion on customer conversion: Evidence from automotive live streaming | |
| A1121: A. Petukhina, M. Basangova, V. Bolovaneanu, A. Conda, A. Melzer, C. Erlwein-Sayer | |
| Day-ahead probability forecasting for redispatch 2.0 measures | |
| A0370: F. Li | |
| Local information advantage and stock returns: Evidence from social media |
| Session EO210 | Room: 106 |
| Recent advances in random matrix theory and high-dimensional statistics | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Jiang Hu | Organizer: Jiang Hu |
| Session EO055 | Room: 108 |
| Recent developments of learning theory | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Dingxuan Zhou | Organizer: Dingxuan Zhou |
| A1066: D. Chen | |
| Functional data analysis | |
| A0271: T. Hu | |
| Sparse online regression algorithm with insensitive loss functions | |
| A0614: F. Lv | |
| On learning with Gaussian kernel | |
| A0865: D. Zhou | |
| Theory of deep convolutional neural networks |
| Session EO235 | Room: 109 |
| Statistical learning based on latent models and graph approaches | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Xu Zhang | Organizer: Xu Zhang |
| A0182: C. Zhou, X. Wang, J. Guo | |
| Learning mixed latent forest models | |
| A0509: R. Luo | |
| Anomaly edge detection in network data using conformal prediction | |
| A0511: Z. Gao | |
| On statistical analysis of high-dimensional factor models |
| Session EO114 | Room: 110 |
| Recent advances in design of experiments and sampling | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Jinyu Yang | Organizer: Min-Qian Liu |
| A0323: J. Yang | |
| Three-orthogonal designs robust to nonnegligible two-factor interactions | |
| A0305: G. Chen, B. Tang | |
| Selecting strong orthogonal arrays by linear allowable level permutations | |
| A0304: S. Wang | |
| An efficient quasi-random sampling for copulas | |
| A0577: L. Yang | |
| Construction of optimal mixed-level uniform designs |
| Session EO224 | Room: 202 |
| Methods for high-dimensional and high frequency data in economics and finance | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Yayi Yan | Organizer: Xingdong Feng |
| A0415: Y. Ge, X. Feng, M. Wu, S. Chen, T. Li | |
| Testing of regression coefficients under over-parameterized model with hidden confounders | |
| A0494: W. Li | |
| An efficient multivariate volatility model for many assets | |
| A0703: X. Song, D. Kim, M. Oh, Y. Wang | |
| Factor overnight GARCH-Ito models | |
| A0705: W. He, M. Xiaoling, W. Zhong, H. Zhu | |
| Multiperiod dynamic portfolio choice: When high dimensionality meets return predictability |
| Session EO103 | Room: 204 |
| Bayesian models and methods for complex data | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Matias Quiroz | Organizer: Matias Quiroz |
| A0348: L. Deng, M.S. Smith, W.O. Maneesoonthorn | |
| Large skew-t copula models and asymmetric dependence in intraday equity returns | |
| A0349: W. Zhang, M.S. Smith, W.O. Maneesoonthorn, R. Loaiza-Maya | |
| Natural gradient hybrid variational inference with application to deep mixed models | |
| A0773: M. Quiroz, R. Kohn, S. Sisson, Y. Yang | |
| A correlated pseudo-marginal approach to doubly intractable problems | |
| A0823: M. Villani, G. Fagerberg, R. Kohn | |
| Bayesian models for locally stationary time series |
| Session EO023 | Room: 209 |
| Recent advances in complex data analysis | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Binyan Jiang | Organizer: Chenlei Leng |
| A0355: J. Shi, F. Wang, Y. Gao, X. Song, H. Wang | |
| Mixture conditional regression with ultrahigh dimensional text data for estimating extralegal factor effects | |
| A0438: Y. Ma | |
| Supervised centrality via sparse network influence regression with an application to 2021 Henan floods social network | |
| A0936: W. Wu, X. Fan | |
| Random interval distillation for detecting multiple changes in dependent dynamic networks | |
| A0940: B. Jiang | |
| A two-way heterogeneity model for dynamic networks | |
| A1065: Y. Fan | |
| Semiparametric analysis of deep ordinal choice models |
| Session EO123 | Room: 210 |
| Applications of spatial econometrics to high-dimensional data | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Yasumasa Matsuda | Organizer: Yasumasa Matsuda |
| A0388: R. Dai, Y. Matsuda, T. Yamagata | |
| Bias-corrections for correlations and heteroskedasticities in large linear panel models with interactive effects | |
| A0450: Y. Matsuda, R. Dai, Y. Wu | |
| Spatial factor models for surface time series | |
| A0611: T. Yoshida | |
| Geographically weighted regression for compositional data | |
| A0808: S.I.-M. Ko, Y. Matsuda, R. Dai, J. Zhang | |
| Asset pricing with co-search interaction |
| Session EO038 | Room: 212 |
| Statistical analyses of complex data structures | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Abhik Ghosh | Organizer: Abhik Ghosh |
| A0207: M. Jaenada, A. Ghosh, L. Pardo | |
| Robust inference for high-dimensional logistic regression | |
| A0256: C. Agostinelli, L. Greco, G. Saraceno | |
| Weighted likelihood methods for torus data | |
| A0257: K. Das | |
| A Bayesian quantile joint modeling of multivariate longitudinal and time-to-event data | |
| A0322: S. Deb, K. Gupta | |
| A divide-and-conquer approach for spatiotemporal analysis of large house price data from Greater London | |
| A0844: A. Basu, S. Roy, A. Ghosh | |
| Robust singular value decomposition |
| Session EO158 | Room: 307 |
| Advances in functional data analysis and machine learning for complex data | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Yuko Araki | Organizer: Yuko Araki |
| A0822: Y. Araki | |
| Comparison of the survival analysis with functional convex clustering and joint model for complex data | |
| A0730: K. Takeshita, Y. Terada | |
| Nonparametric function-on-scalar regression with deep learning | |
| A0452: M. Imaizumi | |
| Statistical analysis on in-context learning | |
| A0505: H. Matsui, Y. Terada | |
| Prediction of trajectory for variable-domain functional data | |
| A0449: D. Kurisu, T. Otsu | |
| Nonparametric inference on Frechet mean and related population objects on manifolds |
| Session EO062 | Room: 313 |
| New advances in complex time series and spatial learning and modelling | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Zudi Lu | Organizer: Zudi Lu |
| A0220: J. Wang | |
| A varying-coefficient model of expected shortfall and its application to mixed-frequency data | |
| A0496: Y. Zhang, Z. Lu | |
| Spatial-temporal synthetic error model of causal analysis with application to policy causal effect evaluation | |
| A0596: Q. Wang | |
| New asymptotics applied to functional coefficient regression and climate sensitivity analysis | |
| A0650: Z. Lu, F. Akashi, Y. Sun, D. Tjoestheim | |
| Nonlinear interpolation for irregularly observed spatial data: Learning from an additive kriging | |
| A0900: F. Rossi, A. Gupta, J. Lee | |
| Testing linearity of network interaction functions |
| Session EO245 | Room: 405 |
| Advances on some theoretical and applied statistics | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Hui Jiang | Organizer: Lei Huang |
| A1016: S. Hu | |
| Adjusted expected improvement for cumulative regret minimization in noisy Bayesian optimization | |
| A1027: J. Wang | |
| Change plane structural equation model | |
| A1038: S. Sun, W.-L. Loh | |
| Fixed-domain asymptotics for Gaussian random fields | |
| A0924: T. Chen, M. Sankaranarayanan, I. Hossain | |
| A distribution-free mixed-integer optimization approach to hierarchical modelling of clustered and longitudinal data | |
| A1124: H. Jiang, L. Huang | |
| Determining the Number of Common Functional Factors with Twice Cross-Validation |
| Session EO167 | Room: 406 |
| Applied probability and optimisation methods in data science | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Sarat Moka | Organizer: Sarat Moka |
| A0352: W. Chen, C. Wang, H. Kanagawa, C. Oates | |
| Stein pi-importance sampling | |
| A1114: L. Chang | |
| Homogeneity and sparsity pursuit using robust adaptive fused lasso | |
| A0237: Q. Wang, R. Casarin, R. Craiu | |
| Markov Switching tensor regression | |
| A0761: S. Moka, Z. Botev, B. Liquet, S. Muller | |
| Optimization methods for best subset selection problem in high-dimensional linear dimension reduction models |
| Session EO063 | Room: 408 |
| High dimensional and complex data analysis with applications | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Su-Yun Huang | Organizer: Su-Yun Huang |
| A0470: X. Dou, S. Kuriki, G.D. Lin, D. Richards | |
| EM estimation of the B-spline Copula with penalized log-likelihood function | |
| A0575: C.-H. Kao | |
| A genetic model for the analysis of quantitative traits in autotetraploid species | |
| A0463: S.-H. Wang, S.-Y. Huang | |
| A geometric algorithm for contrastive principal component analysis in high dimension | |
| A0391: Y. Cheng, Y. Xia, X. Wang | |
| Bayesian multitask learning for medicine recommendation based on online patient reviews | |
| A1123: G. Cao | |
| Generative adversarial models for extreme geospatial downscaling |
| Session EC266 | Room: 111 |
| High-dimensional statistics and econometrics | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: Wanjie Wang | Organizer: EcoSta |
| A0214: W.-C. Hsiao, C.-K. Ing | |
| On high-dimensional data analysis | |
| A0278: Z. Liao | |
| High-dimensional convex nonparametric least squares with Lasso penalty | |
| A0902: M. Demosthenous, C. Gatu, E. Kontoghiorghes | |
| Computational strategies for regression model selection in the high-dimensional case | |
| A0907: H. Chen | |
| Quantile forward regression in high-dimensional distributional counterfactual analysis | |
| A0817: X. Wang | |
| Adaptive detection of change-points for high-dimensional covariance matrices |
| Session EC305 | Room: 207 |
| Applied statistics and econometrics | Thursday 18.7.2024 16:10 - 18:15 |
| Chair: William WL Wong | Organizer: EcoSta |
| Parallel session K: EcoSta2024 | Friday 19.7.2024 | 08:15 - 09:55 |
| Session EV284 | Room: 406 |
| Statistical and financial research (virtual) | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Wenbo Wu | Organizer: EcoSta |
| A1024: Y. Sun, Z. Rios, B. Bean | |
| IANOVA: Multi-sample means comparisons for imprecise interval data | |
| A0925: T. Moriyama | |
| Comparative study on excess distribution estimators in iid settings | |
| A1057: T.-H. Ke, H.-C. Huang, H.-Y. Shih, J.-Y. Zhang, H.C. Huang | |
| Exploring the linkages between ESG ETFs and ESG indices: A weighting analysis |
| Session EO149 | Room: 102 |
| Further developments in financial modelling (virtual) | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Rogemar Mamon | Organizer: Rogemar Mamon |
| A1062: C. Weng | |
| Would a two-benchmark regime be better? | |
| A1068: Y. Zhao | |
| The impact of intermediaries on insurance demand and pricing | |
| A1095: M. Rodrigo | |
| Solution of fixed and free boundary problems for financial derivatives: An embedding approach |
| Session EO314 | Room: 103 |
| Recent advances in genomics and metagenomics data analysis | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Huijuan Zhou | Organizer: Xianyang Zhang |
| A0221: H. Lin | |
| Multigroup analysis of compositions of microbiomes with covariate adjustments and repeated measures | |
| A0223: J. Chen | |
| mPower: A real data-based power analysis tool for microbiome study design | |
| A0600: T. Wang | |
| mbDecoda: A debiased approach to compositional data analysis for microbiome surveys | |
| A0715: Y. Wei, F. Song, K.Y. Yip, Y. Wei | |
| Differential inference for single-cell RNA-sequencing data |
| Session EO216 | Room: 104 |
| New streams in statistics for stochastic processes (virtual) | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Yuta Koike | Organizer: Yuta Koike |
| A0568: K. Fujimori, K. Tsukuda | |
| Two step estimations via the Dantzig selector for ergodic time series models | |
| A0576: J. Yoshida, N. Yoshida | |
| Quasi-maximum likelihood estimation and penalized estimation under non-standard conditions | |
| A0598: T. Shiotani | |
| Modeling lead-lag effects using bivariate Neyman-Scott processes with gamma kernels | |
| A0637: Y. Uehara | |
| Predictive model selection for jump diffusion models |
| Session EO316 | Room: 105 |
| Advances in computational methods for Bayesian statistics | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Quan Zhou | Organizer: Quan Zhou |
| A0855: K. Khare | |
| Asynchronous and distributed data augmentation for massive data settings | |
| A0827: Y. Yang, R. Tang | |
| Adaptivity of diffusion models to manifold structures | |
| A0662: D. Pati | |
| Parallel and sequential coordinate ascent in variational inference | |
| A0547: Q. Qin | |
| Geometric ergodicity of trans-dimensional Markov chain Monte Carlo algorithms |
| Session EO087 | Room: 106 |
| Advances in inference for high-dimensional and clustered data (virtual) | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Chenlu Ke | Organizer: Chenlu Ke |
| Session EO322 | Room: 108 |
| Cutting-edge statistical methods for modern biomedical problems | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Yi Li | Organizer: Yi Li |
| A0227: Y. Li | |
| Meta-analysis by integrating multiple observational studies with multivariate outcomes | |
| A0229: J. Sun | |
| Variable selection for interval-censored failure time data | |
| A0247: E. Ahmed | |
| Post-estimation strategies in high-dimensional data analytics | |
| A0696: X. Guo | |
| Inference on potentially identified subgroups in clinical trials | |
| A1120: L. Tian | |
| Bootstrap cross-validation estimate |
| Session EO050 | Room: 109 |
| New advances in biomedical research with applications to health data | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Yichuan Zhao | Organizer: Yichuan Zhao |
| Session EO223 | Room: 110 |
| Design and subsampling for massive data | Friday 19.7.2024 08:15 - 09:55 |
| Chair: HaiYing Wang | Organizer: HaiYing Wang |
| A0160: Q. Hu | |
| Subsampling strategies for heavily censored reliability big data | |
| A0531: J. Yu | |
| Optimal subsampling for large-scale linear classification | |
| A0542: X. Li, X. Zhu, H. Wang | |
| Distributed logistic regression for massive data with rare events | |
| A0880: C. Zou | |
| Individual and interactive constrained online selection |
| Session EO083 | Room: 111 |
| Recent advances in statistical learning in genetics and genomics | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Tianying Wang | Organizer: Tianying Wang |
| Session EO197 | Room: 202 |
| New advances in nonparametric learning and high-dimensional analysis (virtual) | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Wei Qian | Organizer: Wei Qian |
| A0938: S. Arya | |
| Kernelized epsilon-greedy algorithm for nonparametric bandits with covariates | |
| A1112: C. Ye | |
| High-dimensional learning for multi-sourced matrix data | |
| A0419: P. Zhao, Y. Niu | |
| Bayesian covariate-dependent latent space model with information adaptivity | |
| A1076: W. Qian | |
| A dynamic Bayesian network approach to interbank market |
| Session EO172 | Room: 204 |
| Recent advances in single cell analysis | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Lin Hou | Organizer: Lin Hou |
| A0392: B. Cai | |
| Statistical inference of cell-type proportions estimated from bulk expression data | |
| A1020: X. Yan, Y. Liu, N. Li, J. Qi, G. Xu, J. Zhao, N. Wang, X. Huang, W. Jiang, A. Justet, T. Adams, R. Homer, A. Amei, I. Rosas, N. Kaminski, Z. Wang | |
| SDePER: A hybrid machine learning and regression method to deconvolve spatial barcoding-based transcriptomic data | |
| A1012: Z. Lin | |
| Symmetric graph convolutional auto-encoder for scalable and accurate study of spatial transcriptomics | |
| A1115: X. Ge | |
| A general statistical framework for FDR control in feature screening of single-cell genomics |
| Session EO324 | Room: 207 |
| Recent advancements in the design and analysis of randomized experiments | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Fan Li | Organizer: Fan Li |
| Session EO150 | Room: 209 |
| Complexity in biological, network, and geometric data analysis (virtual) | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Yusha Liu | Organizer: Meng Li |
| A0636: H. Luo | |
| Geometric shapes of the tree-induced partition | |
| A0643: Y. Niu, Y. Ni, D. Pati, B. Mallick | |
| Covariate-assisted Bayesian graph learning for heterogeneous data | |
| A0690: R. Zheng, M. Tang | |
| Limit results for distributed estimation of invariant subspaces in multiple networks inference and PCA | |
| A0786: Y. Liu | |
| A flexible model for correlated count data, with application to multi-condition differential gene expression analyses |
| Session EO056 | Room: 210 |
| Recent advances in modeling complex population data (virtual) | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Alfonso Landeros | Organizer: Esra Kurum |
| Session EO185 | Room: 212 |
| Statistical modeling and inference for large-scale data analysis | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Zhaoxue Tong | Organizer: Zhaoxue Tong |
| A0287: G. Xu, X. Zhu, W. Liu, J. Fan | |
| Two-way homogeneity pursuit for quantile network vector autoregression | |
| A0399: M. Li, T. Cai, M. Liu | |
| Semi-supervised triply robust inductive transfer learning | |
| A0386: Z. Tong, R. Li | |
| Robust estimation of the high-dimensional precision matrix |
| Session EO118 | Room: 307 |
| Semi/nonpar. methods for highly correlated high dimensional data (virtual) | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Inyoung Kim | Organizer: Inyoung Kim |
| A0343: K. Lee, X. Cao | |
| Scalable Bayesian inference on high-dimensional multivariate linear regression | |
| A0743: M. Chen, I. Kim | |
| Semiparametric joint functional graphical regression | |
| A0780: W. Gao, I. Kim | |
| Informed weighted Dirichlet process mixture for functional clustering in highly correlated high-dimensional data | |
| A0872: S. Park | |
| Functional nonconvex penalization kernel smoothing for high-dimensional additive regression |
| Session EO026 | Room: 313 |
| Contemporary approaches to environmental and spatio-temporal statistics | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Pulong Ma | Organizer: Stefano Castruccio |
| A0244: G. Hu | |
| Clustering spatial functional data using a geographically weighted Dirichlet process | |
| A0425: W. Chang, J. Park | |
| Fast computer model calibration using annealed and transformed variational inference | |
| A0860: L. Menicali, S. Castruccio, D. Richter | |
| Physics-informed priors with application to boundary layer velocity | |
| A0892: K. Wang | |
| Modeling large-scale high-resolution spatial-temporal data with deep ESN and SPDE |
| Session EO108 | Room: 405 |
| Recent advances in high dimensional data analysis | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Chi Tim Ng | Organizer: Chi Tim Ng |
| A0273: X. Chen, F. Li | |
| Principal stratification with U-statistics under principal ignorability | |
| A0498: K. Zhang, C.T. Ng | |
| Change-point detection of time-varying Cox model |
| Session EO198 | Room: 408 |
| Advances in statistical network analysis (virtual) | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Keith Levin | Organizer: Keith Levin |
| A0259: M. Schaub, M. Scholkemper, M. Schaub | |
| Node role discovery in networks: Approximating equitable partitions | |
| A0362: B. Leinwand, V. Lyzinski | |
| Likelihood of weight loss or ACRONYM: Augmented degree corrected community reticulately organized network yielding model | |
| A1018: A. Amini | |
| Limits and potentials of graph neural networks: From spectral simplicity to polynomial bounds | |
| A0158: L. Lin | |
| Nonparametric priors for graph matching |
| Session EO321 | Room: 411 (Virtual sessions) |
| Advances in factor analysis | Friday 19.7.2024 08:15 - 09:55 |
| Chair: Alexander Shkolnik | Organizer: Alexander Shkolnik |
| A0882: S. Chib | |
| Structural breaks and factor selection | |
| A0906: Y. Chen | |
| Deflated heteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA | |
| A0846: Y. Lee, A. Shkolnik | |
| Convergence rate of the James-Stein principal component | |
| A1000: A. Shkolnik, H. Gurdogan | |
| The quadratic optimization bias of large covariance matrices |
| Parallel session L: EcoSta2024 | Friday 19.7.2024 | 10:25 - 11:40 |
| Session EO100 | Room: 102 |
| Recent developments in econometric theory | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Cy Sin | Organizer: Cy Sin |
| A0779: J.-C. Liao, X. Song | |
| Specification analysis in quantile regression models with control functions | |
| A0835: Y.-C. Chen, S.-K. Chang, S.-C. Huang | |
| Post-empirical Bayes regression | |
| A0985: C. Sin | |
| On sandwich variance estimation: Bayesian versus frequentist |
| Session EO117 | Room: 103 |
| New developments in the frontiers of precision medicine and data science | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Shanghong Xie | Organizer: Yuanjia Wang |
| A0345: D. Zeng | |
| Fusing individualized treatment rules using auxiliary outcomes | |
| A0418: Y. Zhao, P. Liu | |
| Empirical Likelihood for fair classification | |
| A0527: B. Chakraborty | |
| Innovative trial designs in mobile and digital health using reinforcement learning |
| Session EO144 | Room: 104 |
| Statistical learning in network data | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Tianxi Li | Organizer: Tianxi Li |
| A0190: Y. Zhang, M. Shao | |
| Distribution-free matrix prediction under arbitrary missing pattern | |
| A0709: R. Wang, L. Wang, X. Tong, X. Han | |
| A local perspective in general latent space network models | |
| A0848: W. Du, W. Zhou, T. Li | |
| Informative periphery detection and post-detection inference on weighted directed networks |
| Session EO022 | Room: 105 |
| Modern topics in machine learning | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Yiming Ying | Organizer: Yiming Ying |
| A0587: Z.-C. Guo | |
| Learning theory of spectral algorithms under covariate shift | |
| A0619: X. Guo, Z.-C. Guo, L. Shi | |
| Capacity dependent analysis for functional online learning algorithms | |
| A0666: Y. Ying | |
| Statistical learning theory for stochastic compositional gradient methods |
| Session EO133 | Room: 106 |
| Advances in complex data analysis | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Daren Wang | Organizer: Daren Wang |
| A0704: H. Xu | |
| Changepoint estimation and inference in functional linear regression models | |
| A1055: Z. Zhang, K. Ritscher, O.H. Madrid Padilla | |
| Risk bounds for quantile additive trend filtering | |
| A0426: L. Qiu, D. Ding | |
| Do uncertain rewards still work: The lottery case in live streaming commerce |
| Session EO057 | Room: 108 |
| Trustworthy and efficient statistical learning | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Yao Li | Organizer: Yao Li |
| A0310: Y. Li, X. Li, X. He, M. Cheng | |
| Textual backdoor attack detection | |
| A0321: H. Li, D. Paul, J. Peng, A. Aue | |
| High dimensional general linear hypotheses under a spiked covariance model | |
| A0836: J. Zheng, Y. Yi, S.-C. Lin, M. Zirpoli | |
| Towards classification of covariance matrices via Bures-Wasserstein-based machine learning |
| Session EO037 | Room: 109 |
| Modern statistical methods in machine learning and economics | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Ruoqing Zhu | Organizer: Quefeng Li |
| A0333: R. Zhu, Y. Li, E. Han, W. Zhou, Z. Qi, Y. Cui | |
| Policy learning with continuous actions under unmeasured confounding | |
| A0832: Q. Zheng | |
| Estimation of average treatment effect for survival outcomes with continuous treatment in observational studies | |
| A1072: Z. Chen | |
| Byzantine-robust distributed learning under heterogeneity via convex hull search |
| Session EO021 | Room: 110 |
| Large random matrices and their applications | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Zeng Li | Organizer: Xiucai Ding |
| Session EO233 | Room: 111 |
| Advances on biostatistics | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Hua Shen | Organizer: Hua Shen |
| A0235: R. Deardon | |
| A Bayesian approach to jointly modelling epidemic and behavioral dynamics | |
| A0937: L. Yu, V. Sevilimedu | |
| An improved MC-SIMEX method | |
| A1102: H. Shen | |
| A two-stage method for integrating probability and non-probability samples with misclassified covariates |
| Session EO205 | Room: 204 |
| Integrative approaches in biomedical data analysis | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Xinlei Wang | Organizer: Xinlei Wang |
| Session EO319 | Room: 207 |
| Recent developments in causal inference | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Wei Luo | Organizer: Wei Luo |
| A0303: S. Ma | |
| Inference of continuous treatment effects in large-scale observational data | |
| A0431: Y. Cui, S. Han | |
| Policy learning with distributional welfare | |
| A0585: Y. Zhu, L. Wang, R. Cook | |
| Selection of mediators and dependence structure for high-dimensional causal mediation analysis |
| Session EO119 | Room: 209 |
| Advancing statistical inference in high dimensional and complex data | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Xin Xing | Organizer: Xin Xing |
| Session EO072 | Room: 210 |
| Recent advances in statistical methods for complex data analysis | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Zeya Wang | Organizer: Lingzhou Xue |
| A1003: D. Li | |
| Robust covariance matrix estimation for high-dimensional compositional data with application to sales data analysis | |
| A1052: D. He, Y. Zhou, H. Zou | |
| Robust rank canonical correlation analysis for multivariate survival data | |
| A1069: W. Wang, X. Meng, Y. Cao | |
| Estimation of out-of-sample Sharpe ratio for high dimensional portfolio optimization |
| Session EO313 | Room: 212 |
| Modern multivariate data: Methods, models, and more | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Joshua Cape | Organizer: Joshua Cape |
| A0308: N. Ning | |
| Variable target scalable particle filter | |
| A0460: M. Liu, Y. Chen, Z. Zhang, X. Xing | |
| Disentangled adversarial flow with ensemble learning for multi-source brain connectome analysis | |
| A0757: R. Lunde | |
| On the validity of conformal prediction for network data under non-uniform sampling |
| Session EO042 | Room: 307 |
| Statistics for non-Euclidean data | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Lujia Bai | Organizer: Subhra Sankar Dhar |
| A0748: S.B. Chatla, R. Liu | |
| Inverse regression for spatially distributed functional data | |
| A0404: L. Bai, W. Wu, H. Dette | |
| Testing for white noises in multivariate locally stationary functional time series | |
| A0957: J. Xu, A. Wood, T. Zou | |
| Robust functional principal component analysis for non-Euclidean random objects |
| Session EO178 | Room: 313 |
| Recent advances in stochastic modeling | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Shuyang Bai | Organizer: Shuyang Bai |
| A0396: F. Fang, L. Forastiere, E. Airoldi | |
| Average and conditional inward and outward spillovers of one unit's treatment under network interference | |
| A0820: M. Duker | |
| Breuer-Major theorems for Hilbert space-valued random variables | |
| A1075: H. Tang, S. Bai, S. Deng | |
| On order selection for multivariate extremes via clustering |
| Session EO121 | Room: 405 |
| Another look at financial econometrics | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Shaoran Li | Organizer: Shaoran Li |
| Session EO071 | Room: 406 |
| Advances in mixture model | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Xuwen Zhu | Organizer: Shuchismita Sarkar |
| A0165: X. Zhu, A. Asilkalkan, S. Sarkar | |
| Finite mixture of hidden Markov models for tensor-variate time series data | |
| A0172: S. Sarkar, Y. Zhang, X. Zhu, Y. Chen | |
| On regime changes in text data using hidden Markov model of contaminated vMF distribution | |
| A0210: Y. Zhang, V. Melnykov | |
| On model-based clustering of multivariate categorical sequences |
| Session EO146 | Room: 408 |
| Biomedical and genomic sciences with predictive and inferential modeling | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Shan Yu | Organizer: Shan Yu |
| Session EC265 | Room: 202 |
| Statistical models and inference | Friday 19.7.2024 10:25 - 11:40 |
| Chair: BaoLuo Sun | Organizer: EcoSta |
| Session EP001 | Room: 411 (Virtual sessions) |
| Poster session | Friday 19.7.2024 10:25 - 11:40 |
| Chair: Cristian Gatu | Organizer: EcoSta |
| A0790: B. Li, X. Xiao, Y. Wang | |
| Research on sleep staging based on hidden Markov model | |
| A0950: Y. Zhang, W. Sutherland | |
| Using Kendall Tau to assess the excess co-movement in time series | |
| A0959: S. Jeong, M. Park, Y.H. Um, M. Go | |
| A data-driven new location recommendation system for sustained revenue growth in retail business | |
| A1026: C.H. Lien, Y.Y. Leong | |
| Optimizing spatial cluster detection in small population: A comparative study of smoothing techniques | |
| A1040: M. Go, M. Park | |
| A study on graph neural network-based stock forecasting methods in stock market | |
| A1056: Y. Um, M.K. Lee | |
| Final project cost estimation in EVMS using LMM | |
| A1118: L. Wang | |
| Deep neural networks on nonparametric regression for times series data |
| Parallel session N: EcoSta2024 | Friday 19.7.2024 | 13:10 - 14:25 |
| Session EI005 (Special Invited Session) | Room: 406 |
| Multivariate models and thresholding statistics | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Lixing Zhu | Organizer: Qihua Wang |
| A0150: Q. Zhang | |
| Multivariate spatiotemporal models with low rank coefficient matrix | |
| A0151: Y. Qiu | |
| Gaussian approximation for thresholding statistics |
| Session EO011 | Room: 102 |
| High-frequency econometrics (virtual) | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Donggyu Kim | Organizer: Donggyu Kim |
| Session EO143 | Room: 103 |
| Recent advances in statistical machine learning | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Biao Cai | Organizer: Biao Cai, Emma Jingfei Zhang |
| A0711: B. Dai, C. Li | |
| RankSEG: A consistent ranking-based framework for segmentation | |
| A0745: Y. Qin | |
| Estimation strategies for treatment and spillover effects under network interference | |
| A0801: Z. Tong | |
| Default risk propagation in a multilayer system |
| Session EO219 | Room: 104 |
| Econometrics and ML for network formation and dynamics | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Wenze Li | Organizer: Wenjie Wang |
| A0603: W. Li, L. Dou, M. Li, W. Wang | |
| Trade shock and formula instruments with firm-level network data | |
| A0608: H. Liu, L. Dou, M. Li, W. Wang | |
| Market access and dynamic network formation with firm-level data | |
| A0700: X. Yu, L. Dou, M. Li, W. Wang | |
| Estimating homophily and transitivity in dynamic networks: Evidence from Chinese registered company data |
| Session EO122 | Room: 105 |
| Financial market dynamics and risk assessment innovations | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Heng Xiong | Organizer: Heng Xiong |
| Session EO141 | Room: 108 |
| Recent advances in statistical learning (virtual) | Friday 19.7.2024 13:10 - 14:25 |
| Chair: BaoLuo Sun | Organizer: BaoLuo Sun |
| A0681: W. Li, D. Huang | |
| Using synthetic data to regularize maximum likelihood estimation | |
| A0768: Y. Choi | |
| Covariate-robust clustering | |
| A0813: B. Sun, W. Miao, W. Deshanee | |
| On doubly robust estimation with nonignorable missing data using instrumental variables |
| Session EO138 | Room: 109 |
| Recent developments in survival analysis and transfer learning | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Chun Yin Lee | Organizer: Xingqiu Zhao |
| A0353: S. Li | |
| Semiparametric structural equation models with interval-censored data | |
| A0712: B. He | |
| Deep representation transfer learning for partially linear models | |
| A0645: C.Y. Lee, K.Y. Wong | |
| Survival analysis with a random change-point |
| Session EO130 | Room: 110 |
| Experiment design and reliability optimization | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Dianpeng Wang | Organizer: Yubin Tian |
| A0311: T. Bai, X. He, D. Wang | |
| Adaptive grid designs for classifying monotonic binary simulations | |
| A0893: D. Xu, Y. Tian, D. Wang | |
| Reliability analysis for systems with thermal balance control of internal components | |
| A0647: P.-Y. Chen | |
| Numerical algorithm-aided approaches for analytically finding optimal designs |
| Session EO032 | Room: 111 |
| Recent advances in joint modelling of multi-outcome data | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Christiana Charalambous | Organizer: Christiana Charalambous |
| A0734: X. Yang, J. Pan, C. Charalambous | |
| A joint model with finite-mixture structure for longitudinal and survival data | |
| A0981: Y. Gu, D. Zeng, G. Heiss, D. Lin | |
| Maximum likelihood estimation for semiparametric regression models with interval-censored multistate data | |
| A1080: C. Charalambous | |
| Modelling biomarker variability in joint analysis of longitudinal and time-to-event data |
| Session EO148 | Room: 202 |
| High-dimensional Robust Statistical Inference | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Cheng Wang | Organizer: Cheng Wang |
| A0429: Z. Feng, X. Wang, X. Chen, H. Peng | |
| Robust probabilistic principal component analysis with mixture of exponential power distributions | |
| A0430: J. Zeng, L. Chen | |
| Dimension reduction for extreme regression via contour projection | |
| A0984: S. Luo, Z. Chen, Z. Xu | |
| A portmanteau local feature discrimination approach to the classification with high-dimensional matrix-variate data |
| Session EO315 | Room: 204 |
| Recent advances in Bayesian methodology | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Ning Ning | Organizer: Ning Ning |
| Session EO088 | Room: 207 |
| Statistical methods for causal inference and policy learning | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Yifan Cui | Organizer: Yifan Cui |
| Session EO182 | Room: 209 |
| Recent advances in complex data analysis with heterogeneity | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Ning Wang | Organizer: Ning Wang |
| A0612: J. Huang, N. Wang, L. Zhu | |
| Detecting change points in low-rank tensors via tucker decomposition and one-dimensional series analysis | |
| A0784: N. Wang | |
| Variants of high-dimensional EM algorithm for mixed linear regression | |
| A0812: X. Zhang | |
| Generalized partially functional linear model based on multi-source data |
| Session EO174 | Room: 210 |
| Sequential hypothesis testing and change-point detection | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Liyan Xie | Organizer: Liyan Xie |
| A0224: Y. Ouyang, L. Xie | |
| Continual density ratio estimation for online time series with applications in change detection | |
| A0225: J. Gao, L. Xie, Z. Li | |
| Online correlation change detection for high-dimensional data | |
| A0767: Y. Xing | |
| Sequential multiple testing: An overview of different setups |
| Session EO065 | Room: 212 |
| Advances in Bayesian modeling and computation | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Cheng Li | Organizer: Cheng Li |
| A0268: R. Tang | |
| Robust Bayesian inference on Riemannian submanifold | |
| A0294: X. Yu, A. Cremaschi, M. De Iorio, A. Jasra, S.Q.D. Ooi, X.L.E. Loo, N. Michael | |
| Latent modularity in multi-view data | |
| A0435: C. Zhang | |
| Semi-implicit variational inference with score matching |
| Session EO009 | Room: 313 |
| Advances in time series analysis | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Artem Prokhorov | Organizer: Artem Prokhorov |
| A0754: L. Gadasina, L. Vyunenko, I. Labutkin | |
| Phase spline-analysis for time series dynamics | |
| A0881: Q. Fang, J. Chang, X. Qiao, Q. Yao | |
| On the modelling and prediction of high-dimensional functional time series | |
| A1103: A. Kraevskiy, A. Prokhorov, E. Sokolovskiy | |
| Early warning systems for financial markets of emerging economies |
| Session EO249 | Room: 408 |
| Advances in mathematical data science | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Xin Guo | Organizer: Xin Guo, Lei Shi |
| A0369: Y. Lei | |
| Generalization and optimization of gradient methods for single-layer neural networks | |
| A0536: W. Gao | |
| Smoothed kth power expectile regression with MQ-type function | |
| A0720: D. Xiang, A. Yang, J. Fan, D. Xiang | |
| Online outcome weighted learning with general loss functions |
| Session EO061 | Room: 411 (Virtual sessions) |
| Statistical properties of eigenstructures in high dimensions | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Moritz Jirak | Organizer: Moritz Jirak |
| A0543: N. Parolya, T. Bodnar | |
| Reviving pseudo-inverses: Asymptotic properties of large dimensional generalized inverses with applications | |
| A0920: M. Lopes, N. Doernemann | |
| Tracy-Widom, Gaussian, and bootstrap: Approximations for leading eigenvalues in high-dimensional PCA | |
| A1078: M. Wahl, M. Wahl | |
| Principal component analysis and graph Laplacians in high dimensions |
| Session EC164 | Room: 307 |
| Functional data analysis | Friday 19.7.2024 13:10 - 14:25 |
| Chair: Pavel Krupskiy | Organizer: EcoSta |
| A0326: X. Li | |
| Two-dimensional functional mixed-effect model for repeatedly measured wearable device data | |
| A0930: M. Yu | |
| Modelling German renewable energy data | |
| A0943: Z. Wang, D. Li, X. Qiao | |
| Factor modelling for matrix-variate functional time series in high dimensions |
| Parallel session O: EcoSta2024 | Friday 19.7.2024 | 14:55 - 16:35 |
| Session EO190 | Room: 102 |
| Volatility risk and asset pricing | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Xingzhi Yao | Organizer: Xingzhi Yao |
| A0169: Y. Luo, X. Xue, M. Izzeldin | |
| When MIDAS meets LASSO: The wisdom of low-frequency variables in forecasting value-at-risk and expected shortfall | |
| A0266: S. Qi, X. Su | |
| Diffusive and jump risk premium in China: The role of trading mechanisms | |
| A0307: R. Tao, C. Wese Simen, L. Zhao | |
| A market-level tug of war: Investor heterogeneity and asset pricing | |
| A0477: X. Yao, Z. Li | |
| Correlation risk premium and return predictability |
| Session EO136 | Room: 103 |
| Recent developments in multiple testing | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Bowen Gang | Organizer: Bowen Gang |
| A0590: H. Zhou | |
| Tau-censored weighted Benjamini-Hochberg procedures under independence | |
| A0863: Y. Romano | |
| ML-powered outlier detection: False discovery rate control and derandomization | |
| A1050: Z. Ren, J. Lee | |
| Boosting e-BH via conditional calibration |
| Session EO104 | Room: 104 |
| Complex data: Network, ranking, and spatial panel data | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Wanjie Wang | Organizer: Wanjie Wang |
| A0300: J. Zhang | |
| Consistent community detection in inter-layer dependent multi-layer networks | |
| A0416: Y. Tao, T. Ke | |
| Homogeneity pursuit in ranking inferences based on pairwise comparison data | |
| A0815: W. Wang, Y. Khoo, X. Tong, Y. Wang | |
| Temporal label recovery via manifold learning | |
| A0490: Z. Yang | |
| Multi-dimensional spatial panel data models with fixed effects: Formulation, estimation and inference |
| Session EO179 | Room: 105 |
| Recent advances in incomplete data analysis | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Puying Zhao | Organizer: Puying Zhao |
| A0588: D. Jiang | |
| Modeling developmental trajectories with nonrandomly missing data | |
| A0512: C. Wang, Q. Zheng | |
| Multiply robust estimation for two-part regression models with missing semi-continuous response | |
| A0526: Y. Zhang, W. Cheng, P. Zhao | |
| Equivalence assessment via the difference between two AUCs in a matched-pair design with nonignorable missing endpoints | |
| A1014: Y. Li, P. Zhao, N. Tang | |
| Robust estimation and testing for GARCH models via exponentially tilted empirical likelihood |
| Session EO230 | Room: 106 |
| Recent advances in factor modelling and large-scale time series analysis | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Yong He | Organizer: Wenxin Zhou |
| A0306: X. Zhang, C. Liu, J. Guo, K. Yuen, A. Welsh | |
| Modeling and learning on high-dimensional matrix-variate sequences | |
| A0896: L. Yu | |
| CP factorization for tensor-variate time series | |
| A0921: Y. He | |
| A new non-parametric Kendall's tau for matrix-valued elliptical observations | |
| A0941: J. He, J. Chang, L. Yang, Q. Yao | |
| Modelling matrix time series via a tensor CP-decomposition |
| Session EO253 | Room: 108 |
| Advance in generalization and optimization of machine learning algorithms | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Yunwen Lei | Organizer: Yunwen Lei |
| Session EO236 | Room: 109 |
| Recent developments in theory and applications of statistical learning | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Jun Fan | Organizer: Jun Fan |
| A0795: Z. Fang, J. Fan, Y. Zhang | |
| Generalization analysis of deep CNNs under maximum correntropy criterion | |
| A0799: L. Song | |
| Generalization analysis of deep ReLU networks for functional learning | |
| A0803: Y. Zhou | |
| Covariance test for discretely observed functional data: When and how it works | |
| A0781: K. Cheng | |
| Regularized reduced-rank regression for structured output prediction with vector-valued functions |
| Session EO099 | Room: 110 |
| Recent advances in design and modeling for complex experiments | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Yaping Wang | Organizer: Yaping Wang |
| A0250: Y. Tian | |
| Stratification pattern enumerator and its applications | |
| A0251: B. Jiang | |
| Generalized linear orthogonal arrays and applications to strong orthogonal arrays | |
| A0578: H. Li | |
| Nearly orthogonal Latin hypercube designs with multi-dimensional stratifications | |
| A0631: Z. Liu, M. Ai, H. Dette, J. Yu | |
| A new approach to optimal design under model uncertainty motivated by multi-armed bandits |
| Session EO045 | Room: 111 |
| Factor models and semiparametric models with applications | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Shuai Wang | Organizer: Mengying You |
| Session EO312 | Room: 202 |
| Recent advances in statistical learning | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Xiaohang Wang | Organizer: Xiaohang Wang |
| A0330: Z. Cao | |
| Transporting randomized trial results to estimate counterfactual survival functions in the target populations | |
| A0382: W. Zhang | |
| Feasibility probability of random linear programming | |
| A0501: J. Wu, H. Qi, J. Luo | |
| A comparative study on federated learning in supply chain forecasting: Pareto optimality on accuracy and efficiency | |
| A0694: L. Su, B. Huang | |
| Application of artificial intelligence for medical big data |
| Session EO132 | Room: 204 |
| Recent results in computational statistics and financial time series | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Minh-Ngoc Tran | Organizer: Minh-Ngoc Tran |
| A0267: C. Liu, M.-N. Tran, C. Wang, R. Gerlach, R. Kohn | |
| Data scaling effect of deep learning in financial time series forecasting | |
| A1019: D. Gunawan, A. Pearse, N. Cressie | |
| Hierarchical spatial copula models for large spatial data | |
| A1105: R. Kohn, D. Frazier, C. Drovandi | |
| Calibrated generalized Bayesian inference | |
| A1091: M.-N. Tran, A. Godichon-Baggioni, D. Nguyen, M.-N. Tran | |
| Natural gradient variational Bayes without Fisher matrix analytic calculation and its inversion |
| Session EO239 | Room: 207 |
| Causal inference and machine learning for survival analysis | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Wenbo Wu | Organizer: Wenbo Wu |
| A0653: Y. Ding | |
| Meta-learners to analyze treatment heterogeneity in survival data | |
| A0422: A. Oganisian | |
| Bayesian semiparametric model for sequential treatment decisions with informative timing | |
| A0327: F. Li, X. Chen, L. Hu | |
| A flexible Bayesian g-formula for causal survival analyses with time-dependent confounding | |
| A0752: L. Xia, B. Nan, Y. Li | |
| Debiased lasso for stratified Cox models with application to the national kidney transplant data |
| Session EO237 | Room: 210 |
| Non-parametric statistical methods for complex biomedical data | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Haochang Shou | Organizer: Haochang Shou |
| A0191: F. Zhang | |
| Improving the reproducibility of brain imaging feature selection with weighted regularization | |
| A0639: S. Greven, L. Steyer | |
| Principal component analysis in Bayes spaces for sparsely sampled density functions | |
| A0719: J. Zhang, H. Shou, H. Li | |
| Integration of longitudinal physical activity data from multiple sources |
| Session EO162 | Room: 212 |
| Extreme value statistics in time and space | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Gilles Stupfler | Organizer: Gilles Stupfler |
| A0862: S. Rizzelli, S. Padoan, C. Dombry | |
| Bayesian analysis of peaks over threshold | |
| A0618: A. Usseglio-Carleve, S. Girard, T. Opitz | |
| ANOVEX: Analysis of variability for heavy-tailed extremes | |
| A0798: M. Felix, D. La Vecchia, G. Stupfler | |
| Local stationarity in the extremes | |
| A0581: C. Yan | |
| Analysis of variability in extremes with application in change point detection |
| Session EO077 | Room: 307 |
| Recent progress on functional data analysis | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Weichi Wu | Organizer: Weichi Wu |
| A0939: H. Lian | |
| Communication-efficient distributed functional regression | |
| A0954: C. Zhang | |
| Functional-edged network modeling | |
| A0996: L. Yang, Q. Hu | |
| Statistical inference for functional data over high-dimensional domain | |
| A1005: Y.-F. Li | |
| A nonlinear mixed-effects functional regression model based on variable selection |
| Session EO200 | Room: 313 |
| Recent developments in time series analysis and related topics | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Sangyeol Lee | Organizer: Sangyeol Lee |
| A0341: M. Kim | |
| Maximum likelihood estimation of elliptical multivariate regular variation | |
| A0481: B. Seo | |
| Accelerated failure time model based on nonparametric Gaussian scale mixtures | |
| A0602: Y. Lee, T. Lee | |
| Block wild bootstrap based Ljung-Box test for VAR model with time-varying variance | |
| A0778: S. Lee, J. Kim, J. Lim | |
| Shapley values for identifying fault variables in MSPC | |
| A0702: M. Jo, S. Lee | |
| Robust estimation for bounded bivariate time series models of counts based on density power divergence |
| Session EO151 | Room: 405 |
| Recent advances and challenges in inference and learning | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Ansgar Steland | Organizer: Ansgar Steland |
| A1008: F. Mies, C. Chong | |
| Likelihood asymptotics for stationary Gaussian arrays | |
| A1032: F. Scholze | |
| Weak convergence of the function-indexed sequential empirical process for nonstationary time series | |
| A1046: J. Schnurbus, A.A.Y. Pua, M. Fritsch | |
| An estimator for dynamic linear panel data models based on nonlinear moment conditions | |
| A1088: C. Xu, Y. Xie | |
| Sequential conformal prediction for time series |
| Session EO256 | Room: 408 |
| Econometrics and contemporary issues in economics and finance (virtual) | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Namhyun Kim | Organizer: Namhyun Kim |
| A0659: M. Daniele, P. Kronenberg, T. Reinicke | |
| Optimal predictor and transformation selection for macroeconomic forecasting using variable importance in random forests | |
| A0955: O. Pavlov | |
| Superstar firms and aggregate fluctuations | |
| A1002: N. Kim | |
| Forecasting agricultural land-use in England by using spatially highly resolution data | |
| A0884: P. Wongsa-art | |
| Cross-national comparisons of COVID-19 lockdown effectiveness: The spatial functional data analysis approach |
| Session EO086 | Room: 411 (Virtual sessions) |
| Analytics in finance and insurance | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Tak Kuen Siu | Organizer: Tak Kuen Siu |
| Session EC269 | Room: 406 |
| Financial econometrics | Friday 19.7.2024 14:55 - 16:35 |
| Chair: Wai-keung Li | Organizer: EcoSta |
| A0988: A. Badescu, M. Augustyniak, J.-F. Begin, S.K. Jayaraman | |
| A general option pricing framework for affine fractionally integrated models | |
| A1009: Y. Li, R. Bu, J. Cheng, A. Idi cheffou, F. Jawadi | |
| Extreme movements and volatility regimes: A latent factor regime switching perspective | |
| A0824: T. Tichy, M. Holcapek, D. Nedela | |
| Financial time series analysis with weighted quantile approach | |
| A0708: J. Jiang, R. Huser, J. Richards, D. Bolin | |
| The tail efficiency hypothesis: Extreme-value perspective on market efficiency |