Journal of the American Statistical Association

2008 - 2024

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 119, issue 548, 2024

Statistical Foundations Driving 21st Century Innovation pp. 2427-2436

Katherine B. Ensor

An Efficient Coalescent Model for Heterochronously Sampled Molecular Data pp. 2437-2449

Lorenzo Cappello, Amandine Véber and Julia A. Palacios

Dissecting Gene Expression Heterogeneity: Generalized Pearson Correlation Squares and the K-Lines Clustering Algorithm pp. 2450-2463

Jingyi Jessica Li, Heather J. Zhou, Peter J. Bickel and Xin Tong

Joint Tensor Modeling of Single Cell 3D Genome and Epigenetic Data with Muscle pp. 2464-2477

Kwangmoon Park and Sündüz Keleş

Generalizing the Intention-to-Treat Effect of an Active Control from Historical Placebo-Controlled Trials: A Case Study of the Efficacy of Daily Oral TDF/FTC in the HPTN 084 Study pp. 2478-2492

Qijia He, Fei Gao, Oliver Dukes, Sinead Delany-Moretlwe and Bo Zhang

Efficient Stochastic Generators with Spherical Harmonic Transformation for High-Resolution Global Climate Simulations from CESM2-LENS2 pp. 2493-2507

Yan Song, Zubair Khalid and Marc G. Genton

Sparse Independent Component Analysis with an Application to Cortical Surface fMRI Data in Autism pp. 2508-2520

Zihang Wang, Irina Gaynanova, Aleksandr Aravkin and Benjamin B. Risk

Statistical Inference of Cell-Type Proportions Estimated from Bulk Expression Data pp. 2521-2532

Biao Cai, Jingfei Zhang, Hongyu Li, Chang Su and Hongyu Zhao

Functional Integrative Bayesian Analysis of High-Dimensional Multiplatform Clinicogenomic Data pp. 2533-2547

Rupam Bhattacharyya, Nicholas C. Henderson and Veerabhadran Baladandayuthapani

Ultimate Pólya Gamma Samplers–Efficient MCMC for Possibly Imbalanced Binary and Categorical Data pp. 2548-2559

Gregor Zens, Sylvia Frühwirth-Schnatter and Helga Wagner

Bayesian Inference on High-Dimensional Multivariate Binary Responses pp. 2560-2571

Antik Chakraborty, Rihui Ou and David B. Dunson

Discovery and Inference of a Causal Network with Hidden Confounding pp. 2572-2584

Li Chen, Chunlin Li, Xiaotong Shen and Wei Pan

A Regression-Based Approach to Robust Estimation and Inference for Genetic Covariance pp. 2585-2597

Jianqiao Wang, Sai Li and Hongzhe Li

Copula Modeling of Serially Correlated Multivariate Data with Hidden Structures pp. 2598-2609

Robert Zimmerman, Radu V. Craiu and Vianey Leos-Barajas

The Cellwise Minimum Covariance Determinant Estimator pp. 2610-2621

Jakob Raymaekers and Peter Rousseeuw

Controlling Cumulative Adverse Risk in Learning Optimal Dynamic Treatment Regimens pp. 2622-2633

Mochuan Liu, Yuanjia Wang, Haoda Fu and Donglin Zeng

Latent Space Modeling of Hypergraph Data pp. 2634-2646

Kathryn Turnbull, Simón Lunagómez, Christopher Nemeth and Edoardo Airoldi

Minimax Quasi-Bayesian Estimation in Sparse Canonical Correlation Analysis via a Rayleigh Quotient Function pp. 2647-2657

Qiuyun Zhu and Yves Atchadé

A Projection Space-Filling Criterion and Related Optimality Results pp. 2658-2669

Chenlu Shi and Hongquan Xu

New Estimands for Experiments with Strong Interference pp. 2670-2679

David Choi

Factor Augmented Sparse Throughput Deep ReLU Neural Networks for High Dimensional Regression pp. 2680-2694

Jianqing Fan and Yihong Gu

Uniform Inference for Kernel Density Estimators with Dyadic Data pp. 2695-2708

Matias Cattaneo, Yingjie Feng and William G. Underwood

A General Framework for Circular Local Likelihood Regression pp. 2709-2721

María Alonso-Pena, Irène Gijbels and Rosa M. Crujeiras

Enveloped Huber Regression pp. 2722-2732

Le Zhou, R. Dennis Cook and Hui Zou

Dimension Reduction for Fréchet Regression pp. 2733-2747

Qi Zhang, Lingzhou Xue and Bing Li

Optimal and Safe Estimation for High-Dimensional Semi-Supervised Learning pp. 2748-2759

Siyi Deng, Yang Ning, Jiwei Zhao and Heping Zhang

Higher-Order Expansions and Inference for Panel Data Models pp. 2760-2771

Jiti Gao, Bin Peng and Yayi Yan

Nonparametric Statistical Inference via Metric Distribution Function in Metric Spaces pp. 2772-2784

Xueqin Wang, Jin Zhu, Wenliang Pan, Junhao Zhu and Heping Zhang

In Nonparametric and High-Dimensional Models, Bayesian Ignorability is an Informative Prior pp. 2785-2798

Antonio R. Linero

Testing General Linear Hypotheses Under a High-Dimensional Multivariate Regression Model with Spiked Noise Covariance pp. 2799-2810

Haoran Li, Alexander Aue, Debashis Paul and Jie Peng

Doubly Robust Interval Estimation for Optimal Policy Evaluation in Online Learning pp. 2811-2821

Ye Shen, Hengrui Cai and Rui Song

Split Knockoffs for Multiple Comparisons: Controlling the Directional False Discovery Rate pp. 2822-2832

Yang Cao, Xinwei Sun and Yuan Yao

Bayesian Spline-Based Hidden Markov Models with Applications to Actimetry Data and Sleep Analysis pp. 2833-2843

Sida Chen and Bärbel Finkenstädt

Optimal Subsampling via Predictive Inference pp. 2844-2856

Xiaoyang Wu, Yuyang Huo, Haojie Ren and Changliang Zou

A Decorrelating and Debiasing Approach to Simultaneous Inference for High-Dimensional Confounded Models pp. 2857-2868

Yinrui Sun, Li Ma and Yin Xia

Causal Inference with Noncompliance and Unknown Interference pp. 2869-2880

Tadao Hoshino and Takahide Yanagi

Minimum Resource Threshold Policy Under Partial Interference pp. 2881-2894

Chan Park, Guanhua Chen, Menggang Yu and Hyunseung Kang

Online Regularization toward Always-Valid High-Dimensional Dynamic Pricing pp. 2895-2907

Chi-Hua Wang, Zhanyu Wang, Will Wei Sun and Guang Cheng

Bootstrap Inference in the Presence of Bias pp. 2908-2918

Giuseppe Cavaliere, Sílvia Gonçalves, Morten Nielsen and Edoardo Zanelli

Semi-Distance Correlation and Its Applications pp. 2919-2933

Wei Zhong, Zhuoxi Li, Wenwen Guo and Hengjian Cui

Balancing Covariates in Randomized Experiments with the Gram–Schmidt Walk Design pp. 2934-2946

Christopher Harshaw, Fredrik Sävje, Daniel A. Spielman and Peng Zhang

Bounding Wasserstein Distance with Couplings pp. 2947-2958

Niloy Biswas and Lester Mackey

Model-Robust and Efficient Covariate Adjustment for Cluster-Randomized Experiments pp. 2959-2971

Bingkai Wang, Chan Park, Dylan S. Small and Fan Li

Online Statistical Inference for Stochastic Optimization via Kiefer-Wolfowitz Methods pp. 2972-2982

Xi Chen, Zehua Lai, He Li and Yichen Zhang

Fitting Latent Non-Gaussian Models Using Variational Bayes and Laplace Approximations pp. 2983-2995

Rafael Cabral, David Bolin and Håvard Rue

Dynamic Matrix Recovery pp. 2996-3007

Ziyuan Chen, Ying Yang and Fang Yao

Clustering High-Dimensional Noisy Categorical Data pp. 3008-3019

Zhiyi Tian, Jiaming Xu and Jen Tang

A Kernel Measure of Dissimilarity between M Distributions pp. 3020-3032

Zhen Huang and Bodhisattva Sen

Robust Validation: Confident Predictions Even When Distributions Shift pp. 3033-3044

Maxime Cauchois, Suyash Gupta, Alnur Ali and John C. Duchi

Policy Learning with Asymmetric Counterfactual Utilities pp. 3045-3058

Eli Ben-Michael, Kosuke Imai and Zhichao Jiang

Extremal Random Forests pp. 3059-3072

Nicola Gnecco, Edossa Merga Terefe and Sebastian Engelke

Graphical Principal Component Analysis of Multivariate Functional Time Series pp. 3073-3085

Jianbin Tan, Decai Liang, Yongtao Guan and Hui Huang

A Composite Likelihood-Based Approach for Change-Point Detection in Spatio-Temporal Processes pp. 3086-3100

Zifeng Zhao, Ting Fung Ma, Wai Leong Ng and Chun Yip Yau

Identifiability and Consistent Estimation for Gaussian Chain Graph Models pp. 3101-3112

Ruixuan Zhao, Haoran Zhang and Junhui Wang

Reinforcement Learning in Latent Heterogeneous Environments pp. 3113-3126

Elynn Y. Chen, Rui Song and Michael I. Jordan

Semiparametric Bayesian Inference for Local Extrema of Functions in the Presence of Noise pp. 3127-3140

Meng Li, Zejian Liu, Cheng-Han Yu and Marina Vannucci

Consistent Community Detection in Inter-Layer Dependent Multi-Layer Networks pp. 3141-3151

Jingnan Zhang, Junhui Wang and Xueqin Wang

Federated Offline Reinforcement Learning pp. 3152-3163

Doudou Zhou, Yufeng Zhang, Aaron Sonabend-W, Zhaoran Wang, Junwei Lu and Tianxi Cai

Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison pp. 3164-3182

Lucas Vogels, Reza Mohammadi, Marit Schoonhoven and Ş. İlker Birbil

Structural Equation Modeling Using R/SAS: A Step-by-Step Approach with Real Data Analysis pp. 3183-3184

Lifeng Lin

Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values pp. 3184-3186

Ross L. Prentice

Spatial Statistics for Data Science: Theory and Practice with R pp. 3186-3187

Chae Young Lim

Correction pp. 3188-3188

The Editors

Corrections to “Spatio-Temporal Cross-Covariance Functions under the Lagrangian Framework with Multiple Advections” pp. 3189-3189

The Editors

Volume 119, issue 547, 2024

Weighted Functional Data Analysis for the Calibration of a Ground Motion Model in Italy pp. 1697-1708

Teresa Bortolotti, Riccardo Peli, Giovanni Lanzano, Sara Sgobba and Alessandra Menafoglio

Bayesian Integrative Region Segmentation in Spatially Resolved Transcriptomic Studies pp. 1709-1721

Yinqiao Yan and Xiangyu Luo

Assessing COVID-19 Prevalence in Austria with Infection Surveys and Case Count Data as Auxiliary Information pp. 1722-1735

Stéphane Guerrier, Christoph Kuzmics and Maria-Pia Victoria-Feser

Evaluating Dynamic Conditional Quantile Treatment Effects with Applications in Ridesharing pp. 1736-1750

Ting Li, Chengchun Shi, Zhaohua Lu, Yi Li and Hongtu Zhu

Coexchangeable Process Modeling for Uncertainty Quantification in Joint Climate Reconstruction pp. 1751-1764

Lachlan Astfalck, Daniel Williamson, Niall Gandy, Lauren Gregoire and Ruza Ivanovic

Tree-Guided Rare Feature Selection and Logic Aggregation with Electronic Health Records Data pp. 1765-1777

Jianmin Chen, Robert H. Aseltine, Fei Wang and Kun Chen

An Automated Approach to Causal Inference in Discrete Settings pp. 1778-1793

Guilherme Duarte, Noam Finkelstein, Dean Knox, Jonathan Mummolo and Ilya Shpitser

Asymptotic Distribution-Free Independence Test for High-Dimension Data pp. 1794-1804

Zhanrui Cai, Jing Lei and Kathryn Roeder

Classified Mixed Model Projections pp. 1805-1819

J. Sunil Rao, Mengying Li and Jiming Jiang

Gaussian Approximation and Spatially Dependent Wild Bootstrap for High-Dimensional Spatial Data pp. 1820-1832

Daisuke Kurisu, Kengo Kato and Xiaofeng Shao

Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial Learning pp. 1833-1846

Chengchun Shi, Yunzhe Zhou and Lexin Li

Bayesian Inference Using the Proximal Mapping: Uncertainty Quantification Under Varying Dimensionality pp. 1847-1858

Maoran Xu, Hua Zhou, Yujie Hu and Leo L. Duan

Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness pp. 1859-1870

Kendrick Qijun Li, Xu Shi, Wang Miao and Eric Tchetgen Tchetgen

Bahadur Efficiency of Observational Block Designs pp. 1871-1881

Paul R. Rosenbaum

Exact Bayesian Inference for Diffusion-Driven Cox Processes pp. 1882-1894

Flávio B. Gonçalves, Krzysztof G. Łatuszyński and Gareth O. Roberts

On the Estimation of the Number of Communities for Sparse Networks pp. 1895-1910

Neil Hwang, Jiarui Xu, Shirshendu Chatterjee and Sharmodeep Bhattacharyya

Multivariate Sparse Clustering for Extremes pp. 1911-1922

Nicolas Meyer and Olivier Wintenberger

Spectral Embedding of Weighted Graphs pp. 1923-1932

Ian Gallagher, Andrew Jones, Anna Bertiger, Carey E. Priebe and Patrick Rubin-Delanchy

DDAC-SpAM: A Distributed Algorithm for Fitting High-dimensional Sparse Additive Models with Feature Division and Decorrelation pp. 1933-1944

Yifan He, Ruiyang Wu, Yong Zhou and Yang Feng

Frequency Detection and Change Point Estimation for Time Series of Complex Oscillation pp. 1945-1956

Hau-Tieng Wu and Zhou Zhou

Factor Augmented Inverse Regression and its Application to Microbiome Data Analysis pp. 1957-1967

Daolin Pang, Hongyu Zhao and Tao Wang

Statistical Inference for Maximin Effects: Identifying Stable Associations across Multiple Studies pp. 1968-1984

Zijian Guo

Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data pp. 1985-1999

Yabo Niu, Yang Ni, Debdeep Pati and Bani K. Mallick

Optimal Dynamic Treatment Regimes and Partial Welfare Ordering pp. 2000-2010

Sukjin Han

Value Enhancement of Reinforcement Learning via Efficient and Robust Trust Region Optimization pp. 2011-2025

Chengchun Shi, Zhengling Qi, Jianing Wang and Fan Zhou

Sensitivity to Unobserved Confounding in Studies with Factor-Structured Outcomes pp. 2026-2037

Jiajing Zheng, Jiaxi Wu, Alexander D’Amour and Alexander Franks

High-Dimensional Time Series Segmentation via Factor-Adjusted Vector Autoregressive Modeling pp. 2038-2050

Haeran Cho, Hyeyoung Maeng, Idris A. Eckley and Paul Fearnhead

De-confounding Causal Inference Using Latent Multiple-Mediator Pathways pp. 2051-2065

Yubai Yuan and Annie Qu

Inference in High-Dimensional Multivariate Response Regression with Hidden Variables pp. 2066-2077

Xin Bing, Wei Cheng, Huijie Feng and Yang Ning

Ideal Bayesian Spatial Adaptation pp. 2078-2091

Veronika Ročková and Judith Rousseau

PCABM: Pairwise Covariates-Adjusted Block Model for Community Detection pp. 2092-2104

Sihan Huang, Jiajin Sun and Yang Feng

A Nonstationary Soft Partitioned Gaussian Process Model via Random Spanning Trees pp. 2105-2116

Zhao Tang Luo, Huiyan Sang and Bani Mallick

Empirical Likelihood for Network Data pp. 2117-2128

Yukitoshi Matsushita and Taisuke Otsu

A Comprehensive Bayesian Framework for Envelope Models pp. 2129-2139

Saptarshi Chakraborty and Zhihua Su

Spectral Clustering, Bayesian Spanning Forest, and Forest Process pp. 2140-2153

Leo L. Duan and Arkaprava Roy

Unified Unconditional Regression for Multivariate Quantiles, M-Quantiles, and Expectiles pp. 2154-2165

Luca Merlo, Lea Petrella, Nicola Salvati and Nikos Tzavidis

Semiparametrically Efficient Method for Enveloped Central Space pp. 2166-2177

Linquan Ma, Jixin Wang, Han Chen and Lan Liu

Unveiling the Unobservable: Causal Inference on Multiple Derived Outcomes pp. 2178-2189

Yumou Qiu, Jiarui Sun and Xiao-Hua Zhou

Network Estimation by Mixing: Adaptivity and More pp. 2190-2205

Tianxi Li and Can M. Le

Estimation and Inference of Extremal Quantile Treatment Effects for Heavy-Tailed Distributions pp. 2206-2216

David Deuber, Jinzhou Li, Sebastian Engelke and Marloes H. Maathuis

Latent Multimodal Functional Graphical Model Estimation pp. 2217-2229

Katherine Tsai, Boxin Zhao, Sanmi Koyejo and Mladen Kolar

A Unified Nonparametric Fiducial Approach to Interval-Censored Data pp. 2230-2241

Yifan Cui, Jan Hannig and Michael R. Kosorok

Exact Decoding of a Sequentially Markov Coalescent Model in Genetics pp. 2242-2255

Caleb Ki and Jonathan Terhorst

A Negative Correlation Strategy for Bracketing in Difference-in-Differences pp. 2256-2268

Ting Ye, Luke Keele, Raiden Hasegawa and Dylan S. Small

Nonparametric Finite Mixture: Applications in Overcoming Misclassification Bias pp. 2269-2281

Zi Ye and Solomon W. Harrar

Graphical Model Inference with Erosely Measured Data pp. 2282-2293

Lili Zheng and Genevera I. Allen

Fast Approximation of the Shapley Values Based on Order-of-Addition Experimental Designs pp. 2294-2304

Liuqing Yang, Yongdao Zhou, Haoda Fu, Min-Qian Liu and Wei Zheng

HAC Covariance Matrix Estimation in Quantile Regression pp. 2305-2316

Antonio Galvao and Jungmo Yoon

A Randomized Pairwise Likelihood Method for Complex Statistical Inferences pp. 2317-2327

Gildas Mazo, Dimitris Karlis and Andrea Rau

Group Network Hawkes Process pp. 2328-2344

Guanhua Fang, Ganggang Xu, Haochen Xu, Xuening Zhu and Yongtao Guan

Generalized Bayesian Inference for Discrete Intractable Likelihood pp. 2345-2355

Takuo Matsubara, Jeremias Knoblauch, François-Xavier Briol and Chris. J. Oates

Random Fixed Boundary Flows pp. 2356-2368

Zhigang Yao, Yuqing Xia and Zengyan Fan

Robust Leave-One-Out Cross-Validation for High-Dimensional Bayesian Models pp. 2369-2381

Luca Alessandro Silva and Giacomo Zanella

Spatiotemporal Clustering with Neyman-Scott Processes via Connections to Bayesian Nonparametric Mixture Models pp. 2382-2395

Yixin Wang, Anthony Degleris, Alex Williams and Scott W. Linderman

A Wasserstein Index of Dependence for Random Measures pp. 2396-2406

Marta Catalano, Hugo Lavenant, Antonio Lijoi and Igor Prünster

Smoothness-Penalized Deconvolution (SPeD) of a Density Estimate pp. 2407-2417

David Kent and David Ruppert

Introduction to Environmental Data Science pp. 2418-2419

Timothée Poisot

Controlled Epidemiological Studies pp. 2419-2420

Kaushik Ghosh

Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests pp. 2421-2422

Reza Mohammadi

Statistical Methods in Health Disparity Research pp. 2421-2421

Susan M. Paddock

Corrigendum to Maximum Likelihood Estimation of the Multivariate Normal Mixture Model pp. 2423-2423

The Editors

Volume 119, issue 546, 2024

Partnering With Authors to Enhance Reproducibility at JASA pp. 795-797

Julia Wrobel, Emily C. Hector, Lorin Crawford, Lucy D’Agostino McGowan, Natalia da Silva, Jeff Goldsmith, Stephanie Hicks, Michael Kane, Youjin Lee, Vinicius Mayrink, Christopher J. Paciorek, Therri Usher and Julian Wolfson

Bayesian Landmark-Based Shape Analysis of Tumor Pathology Images pp. 798-810

Cong Zhang, Tejasv Bedi, Chul Moon, Yang Xie, Min Chen and Qiwei Li

Estimating Cell-Type-Specific Gene Co-Expression Networks from Bulk Gene Expression Data with an Application to Alzheimer’s Disease pp. 811-824

Chang Su, Jingfei Zhang and Hongyu Zhao

Leveraging Weather Dynamics in Insurance Claims Triage Using Deep Learning pp. 825-838

Peng Shi, Wei Zhang and Kun Shi

Estimating Trans-Ancestry Genetic Correlation with Unbalanced Data Resources pp. 839-850

Bingxin Zhao, Xiaochen Yang and Hongtu Zhu

Heterogeneity Analysis on Multi-State Brain Functional Connectivity and Adolescent Neurocognition pp. 851-863

Shiying Wang, Todd Constable, Heping Zhang and Yize Zhao

Addressing Multiple Detection Limits with Semiparametric Cumulative Probability Models pp. 864-874

Yuqi Tian, Chun Li, Shengxin Tu, Nathan T. James, FrankE. Harrell and BryanE. Shepherd

Optimal Design of Experiments on Riemannian Manifolds pp. 875-886

Hang Li and Enrique Del Castillo

Two-Way Truncated Linear Regression Models with Extremely Thresholding Penalization pp. 887-903

Hao Yang Teng and Zhengjun Zhang

Valid Model-Free Spatial Prediction pp. 904-914

Huiying Mao, Ryan Martin and Brian J. Reich

Proximal Learning for Individualized Treatment Regimes Under Unmeasured Confounding pp. 915-928

Zhengling Qi, Rui Miao and Xiaoke Zhang

Finite-dimensional Discrete Random Structures and Bayesian Clustering pp. 929-941

Antonio Lijoi, Igor Prünster and Tommaso Rigon

Partially Linear Additive Regression with a General Hilbertian Response pp. 942-956

Sungho Cho, Jeong Min Jeon, Dongwoo Kim, Kyusang Yu and Byeong U. Park

Simultaneous Decorrelation of Matrix Time Series pp. 957-969

Yuefeng Han, Rong Chen, Cun-Hui Zhang and Qiwei Yao

Adaptive Algorithm for Multi-Armed Bandit Problem with High-Dimensional Covariates pp. 970-982

Wei Qian, Ching-Kang Ing and Ji Liu

Confidently Comparing Estimates with the c-value pp. 983-994

Brian L. Trippe, Sameer K. Deshpande and Tamara Broderick

Guaranteed Functional Tensor Singular Value Decomposition pp. 995-1007

Rungang Han, Pixu Shi and Anru R. Zhang

A Random Projection Approach to Hypothesis Tests in High-Dimensional Single-Index Models pp. 1008-1018

Changyu Liu, Xingqiu Zhao and Jian Huang

Higher-Order Least Squares: Assessing Partial Goodness of Fit of Linear Causal Models pp. 1019-1031

Christoph Schultheiss, Peter Bühlmann and Ming Yuan

On Semiparametrically Dynamic Functional-Coefficient Autoregressive Spatio-Temporal Models with Irregular Location Wide Nonstationarity pp. 1032-1043

Zudi Lu, Xiaohang Ren and Rongmao Zhang

Copula Based Cox Proportional Hazards Models for Dependent Censoring pp. 1044-1054

Negera Wakgari Deresa and Ingrid Van Keilegom

Optimal Linear Discriminant Analysis for High-Dimensional Functional Data pp. 1055-1064

Kaijie Xue, Jin Yang and Fang Yao

A General M-estimation Theory in Semi-Supervised Framework pp. 1065-1075

Shanshan Song, Yuanyuan Lin and Yong Zhou

Are Latent Factor Regression and Sparse Regression Adequate? pp. 1076-1088

Jianqing Fan, Zhipeng Lou and Mengxin Yu

Variational Bayes for Fast and Accurate Empirical Likelihood Inference pp. 1089-1101

Weichang Yu and Howard D. Bondell

Kernel Estimation of Bivariate Time-Varying Coefficient Model for Longitudinal Data with Terminal Event pp. 1102-1111

Yue Wang, Bin Nan and John D. Kalbfleisch

Bayesian Robustness: A Nonasymptotic Viewpoint pp. 1112-1123

Kush Bhatia, Yi-An Ma, Anca D. Dragan, Peter L. Bartlett and Michael I. Jordan

Skeleton Clustering: Dimension-Free Density-Aided Clustering pp. 1124-1135

Zeyu Wei and Yen-Chi Chen

A Two-Sample Conditional Distribution Test Using Conformal Prediction and Weighted Rank Sum pp. 1136-1154

Xiaoyu Hu and Jing Lei

Bayesian Modeling with Spatial Curvature Processes pp. 1155-1167

Aritra Halder, Sudipto Banerjee and Dipak K. Dey

Solving Estimating Equations With Copulas pp. 1168-1180

Thomas Nagler and Thibault Vatter

Intraday Periodic Volatility Curves pp. 1181-1191

Torben Andersen, Tao Su, Viktor Todorov and Zhiyuan Zhang

Crowdsourcing Utilizing Subgroup Structure of Latent Factor Modeling pp. 1192-1204

Qi Xu, Yubai Yuan, Junhui Wang and Annie Qu

Nonlinear Causal Discovery with Confounders pp. 1205-1214

Chunlin Li, Xiaotong Shen and Wei Pan

Online Smooth Backfitting for Generalized Additive Models pp. 1215-1228

Ying Yang, Fang Yao and Peng Zhao

Hypotheses Testing from Complex Survey Data Using Bootstrap Weights: A Unified Approach pp. 1229-1239

Jae Kwang Kim, J. N. K. Rao and Zhonglei Wang

Instrumental Variable Estimation of Marginal Structural Mean Models for Time-Varying Treatment pp. 1240-1251

Haben Michael, Yifan Cui, Scott A. Lorch and Eric J. Tchetgen Tchetgen

Factor Modeling for Clustering High-Dimensional Time Series pp. 1252-1263

Bo Zhang, Guangming Pan, Qiwei Yao and Wang Zhou

Network Inference Using the Hub Model and Variants pp. 1264-1273

Zhibing He, Yunpeng Zhao, Peter Bickel, Charles Weko, Dan Cheng and Jirui Wang

Estimation and Inference for High-Dimensional Generalized Linear Models with Knowledge Transfer pp. 1274-1285

Sai Li, Linjun Zhang, T. Tony Cai and Hongzhe Li

On Learning and Testing of Counterfactual Fairness through Data Preprocessing pp. 1286-1296

Haoyu Chen, Wenbin Lu, Rui Song and Pulak Ghosh

Distributed Inference for Spatial Extremes Modeling in High Dimensions pp. 1297-1308

Emily C. Hector and Brian J. Reich

Doubly Robust Capture-Recapture Methods for Estimating Population Size pp. 1309-1321

Manjari Das, Edward H. Kennedy and Nicholas P. Jewell

Variable Selection for High-Dimensional Nodal Attributes in Social Networks with Degree Heterogeneity pp. 1322-1335

Jia Wang, Xizhen Cai, Xiaoyue Niu and Runze Li

Fixed-Domain Posterior Contraction Rates for Spatial Gaussian Process Model with Nugget pp. 1336-1347

Cheng Li, Saifei Sun and Yichen Zhu

Semiparametric Proximal Causal Inference pp. 1348-1359

Yifan Cui, Hongming Pu, Xu Shi, Wang Miao and Eric Tchetgen Tchetgen

Bayesian Conditional Transformation Models pp. 1360-1373

Manuel Carlan, Thomas Kneib and Nadja Klein

Cohesion and Repulsion in Bayesian Distance Clustering pp. 1374-1384

Abhinav Natarajan, Maria De Iorio, Andreas Heinecke, Emanuel Mayer and Simon Glenn

Feature Screening with Conditional Rank Utility for Big-Data Classification pp. 1385-1395

Xingxiang Li and Chen Xu

Test of Significance for High-Dimensional Thresholds with Application to Individualized Minimal Clinically Important Difference pp. 1396-1408

Huijie Feng, Jingyi Duan, Yang Ning and Jiwei Zhao

Scalable Bayesian Transport Maps for High-Dimensional Non-Gaussian Spatial Fields pp. 1409-1423

Matthias Katzfuss and Florian Schäfer

Tail Spectral Density Estimation and Its Uncertainty Quantification: Another Look at Tail Dependent Time Series Analysis pp. 1424-1433

Ting Zhang and Beibei Xu

Cross-Validation: What Does It Estimate and How Well Does It Do It? pp. 1434-1445

Stephen Bates, Trevor Hastie and Robert Tibshirani

Efficient Multimodal Sampling via Tempered Distribution Flow pp. 1446-1460

Yixuan Qiu and Xiao Wang

Inference in High-Dimensional Online Changepoint Detection pp. 1461-1472

Yudong Chen, Tengyao Wang and Richard J. Samworth

Adaptive Functional Thresholding for Sparse Covariance Function Estimation in High Dimensions pp. 1473-1485

Qin Fang, Shaojun Guo and Xinghao Qiao

Statistical Inferences for Complex Dependence of Multimodal Imaging Data pp. 1486-1499

Jinyuan Chang, Jing He, Jian Kang and Mingcong Wu

Sparse Convoluted Rank Regression in High Dimensions pp. 1500-1512

Le Zhou, Boxiang Wang and Hui Zou

Testing Simultaneous Diagonalizability pp. 1513-1525

Yuchen Xu, Marie-Christine Düker and David S. Matteson

A Unified Inference for Predictive Quantile Regression pp. 1526-1540

Xiaohui Liu, Wei Long, Liang Peng and Bingduo Yang

Inference for Treatment-Specific Survival Curves Using Machine Learning pp. 1541-1553

Ted Westling, Alex Luedtke, Peter B. Gilbert and Marco Carone

Anytime-Valid Tests of Conditional Independence Under Model-X pp. 1554-1565

Peter Grünwald, Alexander Henzi and Tyron Lardy

Ridge Regression Under Dense Factor Augmented Models pp. 1566-1578

Yi He

Estimation of Linear Functionals in High-Dimensional Linear Models: From Sparsity to Nonsparsity pp. 1579-1591

Junlong Zhao, Yang Zhou and Yufeng Liu

Censored Interquantile Regression Model with Time-Dependent Covariates pp. 1592-1603

Chi Wing Chu and Tony Sit

Large-Scale Two-Sample Comparison of Support Sets pp. 1604-1618

Haoyu Geng, Xiaolong Cui, Haojie Ren and Changliang Zou

A Hierarchical Expected Improvement Method for Bayesian Optimization pp. 1619-1632

Zhehui Chen, Simon Mak and C. F. Jeff Wu

Narrowest Significance Pursuit: Inference for Multiple Change-Points in Linear Models pp. 1633-1646

Piotr Fryzlewicz

Survival Mixed Membership Blockmodel pp. 1647-1656

Fangda Song, Jing Chu, Shuangge Ma and Yingying Wei

Independence Weights for Causal Inference with Continuous Treatments pp. 1657-1670

Jared D. Huling, Noah Greifer and Guanhua Chen

Markov Bases: A 25 Year Update pp. 1671-1686

Félix Almendra-Hernández, Jesús A. De Loera and Sonja Petrović

Mathematical Foundations of Infinite-Dimensional Statistical Models pp. 1687-1689

Bodhisattva Sen

Theory of Statistical Inference pp. 1689-1690

Somabha Mukherjee

Quantitative Methods for Precision Medicine: Pharmacogenomics in Action pp. 1690-1691

Arthur Berg

Statistical Modeling with R: A Dual Frequentist and Bayesian Approach for Life Scientists pp. 1691-1692

Christian P. Robert

Data Science and Predictive Analytics, 2nd ed pp. 1692-1693

Xing Qiu

Correction pp. 1694-1695

Pavel N. Krivitsky, Pietro Coletti and Niel Hens

Volume 119, issue 545, 2024

Overcoming Repeated Testing Schedule Bias in Estimates of Disease Prevalence pp. 1-13

Patrick M. Schnell, Matthew Wascher and Grzegorz A. Rempala

Heterogeneous Distributed Lag Models to Estimate Personalized Effects of Maternal Exposures to Air Pollution pp. 14-26

Daniel Mork, Marianthi-Anna Kioumourtzoglou, Marc Weisskopf, Brent A. Coull and Ander Wilson

A Semiparametric Inverse Reinforcement Learning Approach to Characterize Decision Making for Mental Disorders pp. 27-38

Xingche Guo, Donglin Zeng and Yuanjia Wang

Hierarchical Neyman-Pearson Classification for Prioritizing Severe Disease Categories in COVID-19 Patient Data pp. 39-51

Lijia Wang, Y. X. Rachel Wang, Jingyi Jessica Li and Xin Tong

A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses with Evaluations on Administrative and Survey Data pp. 52-65

Andrés F. Barrientos, Aaron R. Williams, Joshua Snoke and Claire McKay Bowen

Bayesian Lesion Estimation with a Structured Spike-and-Slab Prior pp. 66-80

Anna Menacher, Thomas E. Nichols, Chris Holmes and Habib Ganjgahi

Operator-Induced Structural Variable Selection for Identifying Materials Genes pp. 81-94

Shengbin Ye, Thomas P. Senftle and Meng Li

Latent Network Structure Learning From High-Dimensional Multivariate Point Processes pp. 95-108

Biao Cai, Jingfei Zhang and Yongtao Guan

Bayesian Markov-Switching Tensor Regression for Time-Varying Networks pp. 109-121

Monica Billio, Roberto Casarin and Matteo Iacopini

Conformal Sensitivity Analysis for Individual Treatment Effects pp. 122-135

Mingzhang Yin, Claudia Shi, Yixin Wang and David M. Blei

Randomization-based Joint Central Limit Theorem and Efficient Covariate Adjustment in Randomized Block 2K Factorial Experiments pp. 136-150

Hanzhong Liu, Jiyang Ren and Yuehan Yang

A New and Unified Family of Covariate Adaptive Randomization Procedures and Their Properties pp. 151-162

Wei Ma, Ping Li, Li-Xin Zhang and Feifang Hu

Heavy-Tailed Density Estimation pp. 163-175

Surya T. Tokdar, Sheng Jiang and Erika L. Cunningham

Nonparametric Estimation of Repeated Densities with Heterogeneous Sample Sizes pp. 176-188

Jiaming Qiu, Xiongtao Dai and Zhengyuan Zhu

Hidden Markov Pólya Trees for High-Dimensional Distributions pp. 189-201

Naoki Awaya and Li Ma

Low-Rank Regression Models for Multiple Binary Responses and their Applications to Cancer Cell-Line Encyclopedia Data pp. 202-216

Seyoung Park, Eun Ryung Lee and Hongyu Zhao

Bias-Correction and Test for Mark-Point Dependence with Replicated Marked Point Processes pp. 217-231

Ganggang Xu, Jingfei Zhang, Yehua Li and Yongtao Guan

Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons pp. 232-245

Chengchun Shi, Shikai Luo, Yuan Le, Hongtu Zhu and Rui Song

Nearly Dimension-Independent Sparse Linear Bandit over Small Action Spaces via Best Subset Selection pp. 246-258

Yi Chen, Yining Wang, Ethan X. Fang, Zhaoran Wang and Runze Li

An Empirical Bayes Approach to Shrinkage Estimation on the Manifold of Symmetric Positive-Definite Matrices pp. 259-272

Chun-Hao Yang, Hani Doss and Baba C. Vemuri

Off-Policy Confidence Interval Estimation with Confounded Markov Decision Process pp. 273-284

Chengchun Shi, Jin Zhu, Shen Ye, Shikai Luo, Hongtu Zhu and Rui Song

Optimal One-Pass Nonparametric Estimation Under Memory Constraint pp. 285-296

Mingxue Quan and Zhenhua Lin

Optimal Nonparametric Inference with Two-Scale Distributional Nearest Neighbors pp. 297-307

Emre Demirkaya, Yingying Fan, Lan Gao, Jinchi Lv, Patrick Vossler and Jingbo Wang

Dynamic Principal Component Analysis in High Dimensions pp. 308-319

Xiaoyu Hu and Fang Yao

Scaled Process Priors for Bayesian Nonparametric Estimation of the Unseen Genetic Variation pp. 320-331

Federico Camerlenghi, Stefano Favaro, Lorenzo Masoero and Tamara Broderick

Selective Inference for Hierarchical Clustering pp. 332-342

Lucy L. Gao, Jacob Bien and Daniela Witten

Subspace Estimation with Automatic Dimension and Variable Selection in Sufficient Dimension Reduction pp. 343-355

Jing Zeng, Qing Mai and Xin Zhang

Fast and Numerically Stable Particle-Based Online Additive Smoothing: The AdaSmooth Algorithm pp. 356-367

Alessandro Mastrototaro, Jimmy Olsson and Johan Alenlöv

An Additive Graphical Model for Discrete Data pp. 368-381

Jun Tao, Bing Li and Lingzhou Xue

Bootstrapping Extreme Value Estimators pp. 382-393

Laurens de Haan and Chen Zhou

Fisher-Pitman Permutation Tests Based on Nonparametric Poisson Mixtures with Application to Single Cell Genomics pp. 394-406

Zhen Miao, Weihao Kong, Ramya Korlakai Vinayak, Wei Sun and Fang Han

Modeling and Active Learning for Experiments with Quantitative-Sequence Factors pp. 407-421

Qian Xiao, Yaping Wang, Abhyuday Mandal and Xinwei Deng

Bayesian Spatial Blind Source Separation via the Thresholded Gaussian Process pp. 422-433

Ben Wu, Ying Guo and Jian Kang

Using SVD for Topic Modeling pp. 434-449

Zheng Tracy Ke and Minzhe Wang

To Adjust or not to Adjust? Estimating the Average Treatment Effect in Randomized Experiments with Missing Covariates pp. 450-460

Anqi Zhao and Peng Ding

Anomaly Detection for a Large Number of Streams: A Permutation-Based Higher Criticism Approach pp. 461-474

Ivo V. Stoepker, Rui M. Castro, Ery Arias-Castro and Edwin van den Heuvel

Assumption-Lean Cox Regression pp. 475-484

Stijn Vansteelandt, Oliver Dukes, Kelly Van Lancker and Torben Martinussen

Learning Coefficient Heterogeneity over Networks: A Distributed Spanning-Tree-Based Fused-Lasso Regression pp. 485-497

Xin Zhang, Jia Liu and Zhengyuan Zhu

An Algebraic Estimator for Large Spectral Density Matrices pp. 498-510

Matteo Barigozzi and Matteo Farnè

Fisher’s Combined Probability Test for High-Dimensional Covariance Matrices pp. 511-524

Xiufan Yu, Danning Li and Lingzhou Xue

Large Scale Prediction with Decision Trees pp. 525-537

Jason M. Klusowski and Peter M. Tian

Distribution of Distances based Object Matching: Asymptotic Inference pp. 538-551

Christoph Alexander Weitkamp, Katharina Proksch, Carla Tameling and Axel Munk

Policy Optimization Using Semiparametric Models for Dynamic Pricing pp. 552-564

Jianqing Fan, Yongyi Guo and Mengxin Yu

Inference in Heavy-Tailed Nonstationary Multivariate Time Series pp. 565-581

Matteo Barigozzi, Giuseppe Cavaliere and Lorenzo Trapani

A Mass-Shifting Phenomenon of Truncated Multivariate Normal Priors pp. 582-596

Shuang Zhou, Pallavi Ray, Debdeep Pati and Anirban Bhattacharya

Causal Inference for Social Network Data pp. 597-611

Elizabeth L. Ogburn, Oleg Sofrygin, Iván Díaz and Mark J. van der Laan

Estimating the Spectral Density at Frequencies Near Zero pp. 612-624

Tucker McElroy and Dimitris N. Politis

Estimating Optimal Infinite Horizon Dynamic Treatment Regimes via pT-Learning pp. 625-638

Wenzhuo Zhou, Ruoqing Zhu and Annie Qu

Statistical Learning for Individualized Asset Allocation pp. 639-649

Yi Ding, Yingying Li and Rui Song

Multi-Task Learning with High-Dimensional Noisy Images pp. 650-663

Xin Ma and Suprateek Kundu

Modeling Point Referenced Spatial Count Data: A Poisson Process Approach pp. 664-677

Diego Morales-Navarrete, Moreno Bevilacqua, Christian Caamaño-Carrillo and Luis M. Castro

Robust Inference and Modeling of Mean and Dispersion for Generalized Linear Models pp. 678-689

Jolien Ponnet, Pieter Segaert, Stefan Van Aelst and Tim Verdonck

Stochastic Convergence Rates and Applications of Adaptive Quadrature in Bayesian Inference pp. 690-700

Blair Bilodeau, Alex Stringer and Yanbo Tang

Nonparametric Two-Sample Tests of High Dimensional Mean Vectors via Random Integration pp. 701-714

Yunlu Jiang, Xueqin Wang, Canhong Wen, Yukang Jiang and Heping Zhang

Robust High-Dimensional Regression with Coefficient Thresholding and Its Application to Imaging Data Analysis pp. 715-729

Bingyuan Liu, Qi Zhang, Lingzhou Xue, Peter X.-K. Song and Jian Kang

Fair Policy Targeting pp. 730-743

Davide Viviano and Jelena Bradic

Projection Test for Mean Vector in High Dimensions pp. 744-756

Wanjun Liu, Xiufan Yu, Wei Zhong and Runze Li

Matching on Generalized Propensity Scores with Continuous Exposures pp. 757-772

Xiao Wu, Fabrizia Mealli, Marianthi-Anna Kioumourtzoglou, Francesca Dominici and Danielle Braun

Recommender Systems: A Review pp. 773-785

Patrick M. LeBlanc, David Banks, Linhui Fu, Mingyan Li, Zhengyu Tang and Qiuyi Wu

Statistical Analytics for Health Data Science with SAS and R pp. 786-787

Ali Rahnavard

Martingale Methods in Statistics pp. 787-789

Insuk Seo

Stable Lévy Processes via Lamperti-Type Representations pp. 789-790

Giacomo Bormetti

Fundamentals of Causal Inference: With R pp. 790-791

Ting Ye

Handbook of Matching and Weighting Adjustments for Causal Inference pp. 791-791

Raymond K. W. Wong

The Journal of the American Statistical Association 2023 Associate Editors pp. 792-793

The Editors