Journal of the American Statistical Association
2008 - 2025
Continuation of Journal of the American Statistical Association. Current editor(s): Xuming He, Jun Liu, Joseph Ibrahim and Alyson Wilson From Taylor & Francis Journals Bibliographic data for series maintained by Chris Longhurst (). Access Statistics for this journal.
Is something missing from the series or not right? See the RePEc data check for the archive and series.
Volume 120, issue 551, 2025
- Identifying Genetic Variants for Brain Connectivity Using Ball Covariance Ranking and Aggregation pp. 1323-1334

- Wei Dai and Heping Zhang
- Estimating Heterogeneous Exposure Effects in the Case-Crossover Design Using BART pp. 1335-1346

- Jacob R. Englert, Stefanie T. Ebelt and Howard H. Chang
- Distributional Outcome Regression via Quantile Functions and its Application to Modelling Continuously Monitored Heart Rate and Physical Activity pp. 1347-1359

- Rahul Ghosal, Sujit K. Ghosh, Jennifer A. Schrack and Vadim Zipunnikov
- Fast Signal Region Detection With Application to Whole Genome Association Studies pp. 1360-1372

- Wei Zhang, Fan Wang and Fang Yao
- Prediction of Cognitive Function via Brain Region Volumes with Applications to Alzheimer’s Disease Based on Space-Factor-Guided Functional Principal Component Analysis pp. 1373-1385

- Shoudao Wen, Yi Li, Dehan Kong and Huazhen Lin
- Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment pp. 1386-1399

- Eli Ben-Michael, D. James Greiner, Kosuke Imai and Zhichao Jiang
- Estimating Heterogeneous Causal Mediation Effects with Bayesian Decision Tree Ensembles pp. 1400-1413

- Angela Ting and Antonio R. Linero
- Who Are We Missing?: A Principled Approach to Characterizing the Underrepresented Population pp. 1414-1423

- Harsh Parikh, Rachael K. Ross, Elizabeth Stuart and Kara E. Rudolph
- Debiasing Watermarks for Large Language Models via Maximal Coupling pp. 1424-1436

- Yangxinyu Xie, Xiang Li, Tanwi Mallick, Weijie Su and Ruixun Zhang
- Deep Fréchet Regression pp. 1437-1448

- Su I Iao, Yidong Zhou and Hans-Georg Müller
- Optimal Transport based Cross-Domain Integration for Heterogeneous Data pp. 1449-1462

- Yubai Yuan, Yijiao Zhang, Babak Shahbaba, Norbert Fortin, Keiland Cooper, Qing Nie and Annie Qu
- Kernel Spectral Joint Embeddings for High-Dimensional Noisy Datasets Using Duo-Landmark Integral Operators pp. 1463-1476

- Xiucai Ding and Rong Ma
- Statistical and Computational Efficiency for Smooth Tensor Estimation with Unknown Permutations pp. 1477-1490

- Chanwoo Lee and Miaoyan Wang
- Modeling Hypergraphs with Diversity and Heterogeneous Popularity pp. 1491-1502

- Xianshi Yu and Ji Zhu
- Federated Adaptive Causal Estimation (FACE) of Target Treatment Effects pp. 1503-1516

- Larry Han, Jue Hou, Kelly Cho, Rui Duan and Tianxi Cai
- Distributional Off-Policy Evaluation in Reinforcement Learning pp. 1517-1530

- Zhengling Qi, Chenjia Bai, Zhaoran Wang and Lan Wang
- When Frictions Are Fractional: Rough Noise in High-Frequency Data pp. 1531-1544

- Carsten H. Chong, Thomas Delerue and Guoying Li
- Robust Bayesian Modeling of Counts with Zero Inflation and Outliers: Theoretical Robustness and Efficient Computation pp. 1545-1557

- Yasuyuki Hamura, Kaoru Irie and Shonosuke Sugasawa
- Evaluation of Binary Classifiers for Asymptotically Dependent and Independent Extremes pp. 1558-1568

- Juliette Legrand, Philippe Naveau and Marco Oesting
- Asymptotic Guarantees for Bayesian Phylogenetic Tree Reconstruction pp. 1569-1579

- Alisa Kirichenko, Luke J. Kelly and Jere Koskela
- Frequency Domain Statistical Inference for High-Dimensional Time Series pp. 1580-1592

- Jonas Krampe and Efstathios Paparoditis
- U-Statistic Reduction: Higher-Order Accurate Risk Control and Statistical-Computational Trade-Off pp. 1593-1606

- Meijia Shao, Dong Xia and Yuan Zhang
- Joint Spectral Clustering in Multilayer Degree-Corrected Stochastic Blockmodels pp. 1607-1620

- Joshua Agterberg, Zachary Lubberts and Jesús Arroyo
- Modeling Preferences: A Bayesian Mixture of Finite Mixtures for Rankings and Ratings pp. 1621-1632

- Michael Pearce and Elena A. Erosheva
- Conformal Prediction for Network-Assisted Regression pp. 1633-1644

- Robert Lunde, Elizaveta Levina and Ji Zhu
- Higher Order Accurate Symmetric Bootstrap Confidence Intervals in High Dimensional Penalized Regression pp. 1645-1656

- Debraj Das, Arindam Chatterjee and S. N. Lahiri
- Sensitivity Analysis for Quantiles of Hidden Biases in Matched Observational Studies pp. 1657-1668

- Dongxiao Wu and Xinran Li
- Simulation-Based, Finite-Sample Inference for Privatized Data pp. 1669-1682

- Jordan Awan and Zhanyu Wang
- Efficient Estimation for Longitudinal Networks via Adaptive Merging pp. 1683-1694

- Haoran Zhang and Junhui Wang
- Robust Inference for Federated Meta-Learning pp. 1695-1710

- Zijian Guo, Xiudi Li, Larry Han and Tianxi Cai
- Deconvolution Density Estimation with Penalized MLE pp. 1711-1723

- Yun Cai, Hong Gu and Toby Kenney
- Partial Quantile Tensor Regression pp. 1724-1735

- Dayu Sun, Limin Peng, Zhiping Qiu, Ying Guo and Amita Manatunga
- Communication-Efficient Distributed Estimation and Inference for Cox’s Model pp. 1736-1746

- Pierre Bayle, Jianqing Fan and Zhipeng Lou
- Matrix GARCH Model: Inference and Application pp. 1747-1762

- Cheng Yu, Dong Li, Feiyu Jiang and Ke Zhu
- High-Dimensional Knockoffs Inference for Time Series Data pp. 1763-1774

- Chien-Ming Chi, Yingying Fan, Ching-Kang Ing and Jinchi Lv
- Bayesian Clustering via Fusing of Localized Densities pp. 1775-1786

- Alexander Dombowsky and David B. Dunson
- Robustifying Likelihoods by Optimistically Re-weighting Data pp. 1787-1798

- Miheer Dewaskar, Christopher Tosh, Jeremias Knoblauch and David B. Dunson
- High-Dimensional Expected Shortfall Regression pp. 1799-1810

- Shushu Zhang, Xuming He, Kean Ming Tan and Wen-Xin Zhou
- Partially Exchangeable Stochastic Block Models for (Node-Colored) Multilayer Networks pp. 1811-1827

- Daniele Durante, Francesco Gaffi, Antonio Lijoi and Igor Prünster
- Phase-Type Distributions for Sieve Estimation pp. 1828-1839

- Hu Xiangbin, Yudong Wang, Zhisheng Ye and Xingqiu Zhao
- A Unified Framework for Residual Diagnostics in Generalized Linear Models and Beyond pp. 1840-1852

- Dungang Liu, Zewei Lin and Heping Zhang
- Estimation and Inference of Quantile Spatially Varying Coefficient Models Over Complicated Domains pp. 1853-1867

- Myungjin Kim, Li Wang and Huixia Judy Wang
- Geometric Ergodicity of Trans-Dimensional Markov Chain Monte Carlo Algorithms pp. 1868-1878

- Qian Qin
- Geodesic Mixed Effects Models for Repeatedly Observed/Longitudinal Random Objects pp. 1879-1892

- Satarupa Bhattacharjee and Hans-Georg Müller
- Adaptive Testing for High-Dimensional Data pp. 1893-1905

- Yangfan Zhang, Runmin Wang and Xiaofeng Shao
- When Composite Likelihood meets Stochastic Approximation pp. 1906-1918

- Giuseppe Alfonzetti, Ruggero Bellio, Yunxiao Chen and Irini Moustaki
- Network Goodness-of-Fit for the Block-Model Family pp. 1919-1932

- Jiashun Jin, Zheng Tracy Ke, Jiajun Tang and Jingming Wang
- High-Dimensional Variable Clustering based on Maxima of a Weakly Dependent Random Process pp. 1933-1944

- Alexis Boulin, Elena Di Bernardino, Thomas Laloë and Gwladys Toulemonde
- Simultaneous Inference for Generalized Linear Models with Unmeasured Confounders pp. 1945-1959

- Jin-Hong Du, Larry Wasserman and Kathryn Roeder
- Statistical Inference for High-Dimensional Spectral Density Matrix pp. 1960-1974

- Jinyuan Chang, Qing Jiang, Tucker McElroy and Xiaofeng Shao
- Cutting Feedback in Misspecified Copula Models pp. 1975-1989

- Michael Stanley Smith, Weichang Yu, David J. Nott and David T. Frazier
- Deep Mutual Density Ratio Estimation with Bregman Divergence and Its Applications pp. 1990-2001

- Dongxiao Han, Siming Zheng, Guohao Shen, Xinyuan Song, Liuquan Sun and Jian Huang
- Spatial Linear Models for Environmental Data pp. 2002-2003

- Bruno Sansó
- Generalized Linear Mixed Models: Modern Concepts, Methods and Applications, 2nd ed pp. 2003-2005

- Xing Liu
- Ordinal Data Analysis: Statistical Perspective with Applications pp. 2005-2007

- Maria Iannario
- Statistical Prediction and Machine Learning pp. 2007-2009

- Michal Pešta
- Financial Data Analytics with R: Monte-Carlo Validation pp. 2009-2010

- Tony Sit
- Correction pp. 2011-2014

- The Editors
Volume 120, issue 550, 2025
- Space-Time Extremes of Severe U.S. Thunderstorm Environments pp. 591-604

- Jonathan Koh, Erwan Koch and Anthony C. Davison
- Testing a Large Number of Composite Null Hypotheses Using Conditionally Symmetric Multidimensional Gaussian Mixtures in Genome-Wide Studies pp. 605-617

- Ryan Sun, Zachary R. McCaw and Xihong Lin
- A Physics-Informed, Deep Double Reservoir Network for Forecasting Boundary Layer Velocity pp. 618-630

- Matthew Bonas, David H. Richter and Stefano Castruccio
- ℓ1-based Bayesian Ideal Point Model for Multidimensional Politics pp. 631-644

- Sooahn Shin, Johan Lim and Jong Hee Park
- Spatio-Temporal Modeling for Record-Breaking Temperature Events in Spain pp. 645-657

- Jorge Castillo-Mateo, Alan E. Gelfand, Zeus Gracia-Tabuenca, Jesús Asín and Ana C. Cebrián
- Unlocking Retrospective Prevalent Information in EHRs—A Revisit to the Pairwise Pseudolikelihood pp. 658-670

- Nir Keret and Malka Gorfine
- Immune Profiling Among Colorectal Cancer Subtypes Using Dependent Mixture Models pp. 671-684

- Yunshan Duan, Shuai Guo, Wenyi Wang and Peter Müller
- Inferring Causal Effect of a Digital Communication Strategy under a Latent Sequential Ignorability Assumption and Treatment Noncompliance pp. 685-697

- Yuki Ohnishi, Bikram Karmakar and Wreetabrata Kar
- Combining Broad and Narrow Case Definitions in Matched Case-Control Studies: Firearms in the Home and Suicide Risk pp. 698-709

- Ting Ye, Kan Chen and Dylan Small
- GeoWarp: Warped Spatial Processes for Inferring Subsea Sediment Properties pp. 710-722

- Michael Bertolacci, Andrew Zammit-Mangion, Juan Valderrama Giraldo, Michael O’Neill, Fraser Bransby and Phil Watson
- Sparse Bayesian Group Factor Model for Feature Interactions in Multiple Count Tables Data pp. 723-736

- Shuangjie Zhang, Yuning Shen, Irene A. Chen and Juhee Lee
- Rate-Optimal Rank Aggregation with Private Pairwise Rankings pp. 737-750

- Shirong Xu, Will Wei Sun and Guang Cheng
- Population-Level Balance in Signed Networks pp. 751-763

- Weijing Tang and Ji Zhu
- Node-Level Community Detection within Edge Exchangeable Models for Interaction Processes pp. 764-778

- Yuhua Zhang and Walter Dempsey
- Distributed Heterogeneity Learning for Generalized Partially Linear Models with Spatially Varying Coefficients pp. 779-793

- Shan Yu, Guannan Wang and Li Wang
- Mediation Analysis with the Mediator and Outcome Missing Not at Random pp. 794-804

- Shuozhi Zuo, Debashis Ghosh, Peng Ding and Fan Yang
- False Discovery Rate Control For Structured Multiple Testing: Asymmetric Rules And Conformal Q-values pp. 805-817

- Zinan Zhao and Wenguang Sun
- Nonparametric Multiple-Output Center-Outward Quantile Regression pp. 818-832

- Eustasio del Barrio, Alberto González Sanz and Marc Hallin
- Test and Measure for Partial Mean Dependence Based on Machine Learning Methods pp. 833-845

- Leheng Cai, Xu Guo and Wei Zhong
- Tyranny-of-the-Minority Regression Adjustment in Randomized Experiments pp. 846-858

- Xin Lu and Hanzhong Liu
- Enhanced Response Envelope via Envelope Regularization pp. 859-868

- Oh-Ran Kwon and Hui Zou
- Supervised Dynamic PCA: Linear Dynamic Forecasting with Many Predictors pp. 869-883

- Zhaoxing Gao and Ruey S. Tsay
- Synthetic Likelihood in Misspecified Models pp. 884-895

- David T. Frazier, David J. Nott and Christopher Drovandi
- Contextual Dynamic Pricing with Strategic Buyers pp. 896-908

- Pangpang Liu, Zhuoran Yang, Zhaoran Wang and Will Wei Sun
- Statistical Inference for Hüsler–Reiss Graphical Models Through Matrix Completions pp. 909-921

- Manuel Hentschel, Sebastian Engelke and Johan Segers
- Robust Matrix Completion with Heavy-Tailed Noise pp. 922-934

- Bingyan Wang and Jianqing Fan
- Controlling the False Split Rate in Tree-Based Aggregation pp. 935-947

- Simeng Shao, Jacob Bien and Adel Javanmard
- Optimal Network Membership Estimation under Severe Degree Heterogeneity pp. 948-962

- Zheng Tracy Ke and Jingming Wang
- Parallel Sampling of Decomposable Graphs Using Markov Chains on Junction Trees pp. 963-975

- Mohamad Elmasri
- Efficient Multiple Change Point Detection and Localization For High-Dimensional Quantile Regression with Heteroscedasticity pp. 976-989

- Xianru Wang, Bin Liu, Xinsheng Zhang and Yufeng Liu
- Natural Gradient Variational Bayes Without Fisher Matrix Analytic Calculation and Its Inversion pp. 990-1001

- A. Godichon-Baggioni, D. Nguyen and M.-N. Tran
- Robust Regression with Covariate Filtering: Heavy Tails and Adversarial Contamination pp. 1002-1013

- Ankit Pensia, Varun Jog and Po-Ling Loh
- Statistical Inference for Networks of High-Dimensional Point Processes pp. 1014-1024

- Xu Wang, Mladen Kolar and Ali Shojaie
- Euclidean Mirrors and Dynamics in Network Time Series pp. 1025-1036

- Avanti Athreya, Zachary Lubberts, Youngser Park and Carey Priebe
- Semi-Supervised Triply Robust Inductive Transfer Learning pp. 1037-1047

- Tianxi Cai, Mengyan Li and Molei Liu
- Optimal Network Pairwise Comparison pp. 1048-1062

- Jiashun Jin, Zheng Tracy Ke, Shengming Luo and Yucong Ma
- Monte Carlo Inference for Semiparametric Bayesian Regression pp. 1063-1076

- Daniel R. Kowal and Bohan Wu
- Zigzag Path Connects Two Monte Carlo Samplers: Hamiltonian Counterpart to a Piecewise Deterministic Markov Process pp. 1077-1089

- Akihiko Nishimura, Zhenyu Zhang and Marc A. Suchard
- Model-Based Causal Feature Selection for General Response Types pp. 1090-1101

- Lucas Kook, Sorawit Saengkyongam, Anton Rask Lundborg, Torsten Hothorn and Jonas Peters
- Off-Policy Evaluation in Doubly Inhomogeneous Environments pp. 1102-1114

- Zeyu Bian, Chengchun Shi, Zhengling Qi and Lan Wang
- Improving Tensor Regression by Optimal Model Averaging pp. 1115-1126

- Qiushi Bu, Hua Liang, Xinyu Zhang and Jiahui Zou
- Valid Inference After Causal Discovery pp. 1127-1138

- Paula Gradu, Tijana Zrnic, Yixin Wang and Michael I. Jordan
- Robust Estimation for Number of Factors in High Dimensional Factor Modeling via Spearman Correlation Matrix pp. 1139-1151

- Jiaxin Qiu, Zeng Li and Jianfeng Yao
- On Optimality of Mallows Model Averaging pp. 1152-1163

- Jingfu Peng, Yang Li and Yuhong Yang
- Neyman-Pearson Multi-Class Classification via Cost-Sensitive Learning pp. 1164-1177

- Ye Tian and Yang Feng
- Model-Based Clustering of Categorical Data Based on the Hamming Distance pp. 1178-1188

- Raffaele Argiento, Edoardo Filippi-Mazzola and Lucia Paci
- Large-Scale Low-Rank Gaussian Process Prediction with Support Points pp. 1189-1200

- Yan Song, Wenlin Dai and Marc G. Genton
- An Adaptive Transfer Learning Framework for Functional Classification pp. 1201-1213

- Caihong Qin, Jinhan Xie, Ting Li and Yang Bai
- Estimating Higher-Order Mixed Memberships via the l2,∞ Tensor Perturbation Bound pp. 1214-1224

- Joshua Agterberg and Anru R. Zhang
- A Model-Agnostic Graph Neural Network for Integrating Local and Global Information pp. 1225-1238

- Wenzhuo Zhou, Annie Qu, Keiland W. Cooper, Norbert Fortin and Babak Shahbaba
- Inferring Covariance Structure from Multiple Data Sources via Subspace Factor Analysis pp. 1239-1253

- Noirrit Kiran Chandra, David B. Dunson and Jason Xu
- Adaptive Learning of the Latent Space of Wasserstein Generative Adversarial Networks pp. 1254-1266

- Yixuan Qiu, Qingyi Gao and Xiao Wang
- Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models pp. 1267-1280

- Pascal Kündig and Fabio Sigrist
- A Sparse Beta Regression Model for Network Analysis pp. 1281-1293

- Stefan Stein, Rui Feng and Chenlei Leng
- Robust Permutation Tests in Linear Instrumental Variables Regression pp. 1294-1304

- Purevdorj Tuvaandorj
- Deep Regression Learning with Optimal Loss Function pp. 1305-1317

- Xuancheng Wang, Ling Zhou and Huazhen Lin
- Handbook of Bayesian, Fiducial, and Frequentist Inference pp. 1318-1320

- Mengyang Gu
- Soccer Analytics: An Introduction Using R pp. 1320-1321

- Alexander Aue
- Objective Bayesian Inference pp. 1321-1322

- Jaeyong Lee
Volume 120, issue 549, 2025
- Our Mission in Action: Past, Present, and Future pp. 1-6

- Dionne L. Price
- Poisson-FOCuS: An Efficient Online Method for Detecting Count Bursts with Application to Gamma Ray Burst Detection pp. 7-19

- Kes Ward, Giuseppe Dilillo, Idris Eckley and Paul Fearnhead
- Discussion of “Poisson-FOCuS: An Efficient Online Method for Detecting Count Bursts with Application to Gamma Ray Burst Detection” pp. 20-21

- Mikael Kuusela
- A Space Astrophysics Perspective on Poisson-FOCuS pp. 22-25

- Carlo Graziani
- Discussion on “Poisson-FOCuS: An Efficient Online Method for Detecting Count Bursts with Application to Gamma Ray Burst Detection” by Ward, Dilillo, Eckley and Fearnhead pp. 26-30

- Yang Chen
- Saha and Ramdas’ Discussion of “Poisson-FOCuS” by Ward, Dilillo, Eckley & Fearnhead pp. 31-33

- Aytijhya Saha and Aaditya Ramdas
- Poisson-FOCuS: An Efficient Online Method for Detecting Count Bursts with Application to Gamma Ray Burst Detection. Rejoinder pp. 34-37

- Kes Ward, Giuseppe Dilillo, Idris Eckley and Paul Fearnhead
- Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects pp. 38-51

- Steve Yadlowsky, Scott Fleming, Nigam Shah, Emma Brunskill and Stefan Wager
- Bisection Grover’s Search Algorithm and Its Application in Analyzing CITE-seq Data pp. 52-63

- Ping Ma, Yongkai Chen, Haoran Lu and Wenxuan Zhong
- Using Penalized Synthetic Controls on Truncated Data: A Case Study on Effect of Marijuana Legalization on Direct Payments to Physicians by Opioid Manufacturers pp. 64-79

- Bikram Karmakar, Gourab Mukherjee and Wreetabrata Kar
- Spatial Modeling and Future Projection of Extreme Precipitation Extents pp. 80-95

- Peng Zhong, Manuela Brunner, Thomas Opitz and Raphaël Huser
- Quantification of Vaccine Waning as a Challenge Effect pp. 96-106

- Matias Janvin and Mats J. Stensrud
- Additive Covariance Matrix Models: Modeling Regional Electricity Net-Demand in Great Britain pp. 107-119

- V. Gioia, M. Fasiolo, J. Browell and R. Bellio
- eDNAPlus: A Unifying Modeling Framework for DNA-based Biodiversity Monitoring pp. 120-134

- Alex Diana, Eleni Matechou, Jim Griffin, Douglas W. Yu, Mingjie Luo, Marie Tosa, Alex Bush and Richard A. Griffiths
- Data Fission: Splitting a Single Data Point pp. 135-146

- James Leiner, Boyan Duan, Larry Wasserman and Aaditya Ramdas
- Discussion of “Data Fission: Splitting a Single Data Point” – Some Asymptotic Results for Data Fission pp. 147-150

- Lihua Lei
- Discussion of “Data Fission: Splitting a Single Data Point” pp. 151-157

- Anna Neufeld, Ameer Dharamshi, Lucy L. Gao, Daniela Witten and Jacob Bien
- A Discussion on: “Data Fission: Splitting a Single Data Point” by Leiner, J., Duan, B., Wasserman, L. and Ramdas, A pp. 158-158

- Marta Catalano, Augusto Fasano, Matteo Giordano and Giovanni Rebaudo
- Data Fission and Sampling Designs: A Discussion pp. 159-160

- Kwun Chuen Gary Chan, Ross L. Prentice and Zhenman Yuan
- Assumption-Lean Data Fission with Resampled Data pp. 161-161

- Kevin Fry, Snigdha Panigrahi and Jonathan Taylor
- Discussion of Leiner et al. “Data Fission: Splitting a Single Data Point” pp. 162-163

- Daniel García Rasines and Alastair Young
- Comment for “Data Fission: Splitting a Single Data Point” pp. 164-164

- Sangwon Hyun
- Empirical Bayes Estimation via Data Fission pp. 165-166

- Nikolaos Ignatiadis and Dennis L. Sun
- Comment on “Data Fission: Splitting a Single Data Point” by James Leiner, Boyan Duan, Larry Wasserman and Aaditya Ramdas pp. 167-167

- V. Roshan Joseph
- Discussion of “Data Fission: Splitting a Single Data Point” by Leiner et al pp. 168-169

- Jing Lei, Natalia L. Oliveira and Ryan J. Tibshirani
- Comments on “Data Fission: Splitting a Single Data Point” pp. 170-171

- Sanat K. Sarkar
- Comment on “Data Fission: Splitting a Single Data Point” pp. 172-173

- Philip Waggoner
- Comment on “Data Fission: Splitting a Single Data Point” Data Fission for Unsupervised Learning: A Discussion on Post-Clustering Inference and the Challenges of Debiasing pp. 174-175

- Changhu Wang, Xinzhou Ge, Dongyuan Song and Jingyi Jessica Li
- Comments on “Data Fission: Splitting a Single Data Point” by James Leiner, Boyan Duan, Larry Wasserman, and Aaditya Ramdas pp. 176-177

- Lijun Wang and Hongyu Zhao
- Discussion on “Data Fission: Splitting a Single Data Point” pp. 178-179

- Zhigen Zhao
- Rejoinder pp. 180-185

- James Leiner, Boyan Duan, Larry Wasserman and Aaditya Ramdas
- Model-Free Statistical Inference on High-Dimensional Data pp. 186-197

- Xu Guo, Runze Li, Zhe Zhang and Changliang Zou
- Stochastic Low-Rank Tensor Bandits for Multi-Dimensional Online Decision Making pp. 198-211

- Jie Zhou, Botao Hao, Zheng Wen, Jingfei Zhang and Will Wei Sun
- An Interpretable and Efficient Infinite-Order Vector Autoregressive Model for High-Dimensional Time Series pp. 212-225

- Yao Zheng
- Confidence Intervals for Parameters of Unobserved Events pp. 226-236

- Amichai Painsky
- Ranking Inferences Based on the Top Choice of Multiway Comparisons pp. 237-250

- Jianqing Fan, Zhipeng Lou, Weichen Wang and Mengxin Yu
- Modeling Recurrent Failures on Large Directed Networks pp. 251-265

- Qingqing Zhai, Zhisheng Ye, Cheng Li, Matthew Revie and David B. Dunson
- Robust Personalized Federated Learning with Sparse Penalization pp. 266-277

- Weidong Liu, Xiaojun Mao, Xiaofei Zhang and Xin Zhang
- Doubly Flexible Estimation under Label Shift pp. 278-290

- Seong-ho Lee, Yanyuan Ma and Jiwei Zhao
- Extreme Value Statistics in Semi-Supervised Models pp. 291-304

- Hanan Ahmed, John H.J. Einmahl and Chen Zhou
- CARE: Large Precision Matrix Estimation for Compositional Data pp. 305-317

- Shucong Zhang, Huiyuan Wang and Wei Lin
- Automatic Regenerative Simulation via Non-Reversible Simulated Tempering pp. 318-330

- Miguel Biron-Lattes, Trevor Campbell and Alexandre Bouchard-Côté
- Doubly-Valid/Doubly-Sharp Sensitivity Analysis for Causal Inference with Unmeasured Confounding pp. 331-342

- Jacob Dorn, Kevin Guo and Nathan Kallus
- Statistical Inference For Noisy Matrix Completion Incorporating Auxiliary Information pp. 343-355

- Shujie Ma, Po-Yao Niu, Yichong Zhang and Yinchu Zhu
- Generalized Bayesian Additive Regression Trees Models: Beyond Conditional Conjugacy pp. 356-369

- Antonio R. Linero
- Inferring Independent Sets of Gaussian Variables after Thresholding Correlations pp. 370-381

- Arkajyoti Saha, Daniela Witten and Jacob Bien
- Efficient Nonparametric Estimation of Stochastic Policy Effects with Clustered Interference pp. 382-394

- Chanhwa Lee, Donglin Zeng and Michael G. Hudgens
- Sharp-SSL: Selective High-Dimensional Axis-Aligned Random Projections for Semi-Supervised Learning pp. 395-407

- Tengyao Wang, Edgar Dobriban, Milana Gataric and Richard J. Samworth
- Sobolev Calibration of Imperfect Computer Models pp. 408-418

- Qingwen Zhang and Wenjia Wang
- Modeling and Learning on High-Dimensional Matrix-Variate Sequences pp. 419-434

- Xu Zhang, Catherine C. Liu, Jianhua Guo, K. C. Yuen and A. H. Welsh
- Selection and Aggregation of Conformal Prediction Sets pp. 435-447

- Yachong Yang and Arun Kumar Kuchibhotla
- Testing the Number of Common Factors by Bootstrapped Sample Covariance Matrix in High-Dimensional Factor Models pp. 448-459

- Long Yu, Peng Zhao and Wang Zhou
- Controlled Discovery and Localization of Signals via Bayesian Linear Programming pp. 460-471

- Asher Spector and Lucas Janson
- Tests for Large-Dimensional Shape Matrices via Tyler’s M Estimators pp. 472-485

- Runze Li, Weiming Li and Qinwen Wang
- Graph-Aligned Random Partition Model (GARP) pp. 486-497

- Giovanni Rebaudo and Peter Müller
- Randomness of Shapes and Statistical Inference on Shapes via the Smooth Euler Characteristic Transform pp. 498-510

- Kun Meng, Jinyu Wang, Lorin Crawford and Ani Eloyan
- Generalized Data Thinning Using Sufficient Statistics pp. 511-523

- Ameer Dharamshi, Anna Neufeld, Keshav Motwani, Lucy L. Gao, Daniela Witten and Jacob Bien
- Doubly Robust Augmented Model Accuracy Transfer Inference with High Dimensional Features pp. 524-534

- Doudou Zhou, Molei Liu, Mengyan Li and Tianxi Cai
- Neural Networks for Geospatial Data pp. 535-547

- Wentao Zhan and Abhirup Datta
- Rational Kriging pp. 548-558

- V. Roshan Joseph
- Distribution-Free Prediction Intervals Under Covariate Shift, With an Application to Causal Inference pp. 559-571

- Jing Qin, Yukun Liu, Moming Li and Chiung-Yu Huang
- Operationalizing Legislative Bodies: A Methodological and Empirical Perspective with a Bayesian Approach pp. 572-583

- Carolina Luque and Juan Sosa
- Model-Based Machine Learning pp. 584-585

- Emanuela Furfaro
- ROC Analysis for Classification and Prediction in Practice pp. 585-586

- Mauricio Tec
- Bayesian Nonparametrics for Causal Inference and Missing Data pp. 586-587

- P. Richard Hahn
- Probability Modeling and Statistical Inference in Cancer Screening pp. 587-588

- Li C. Cheung
- Functional Data Analysis with R pp. 588-590

- Piotr S. Kokoszka
| |