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Content
April 2024, Volume 119, Issue 546
- 875-886 Optimal Design of Experiments on Riemannian Manifolds
by Hang Li & Enrique Del Castillo - 887-903 Two-Way Truncated Linear Regression Models with Extremely Thresholding Penalization
by Hao Yang Teng & Zhengjun Zhang - 904-914 Valid Model-Free Spatial Prediction
by Huiying Mao & Ryan Martin & Brian J. Reich - 915-928 Proximal Learning for Individualized Treatment Regimes Under Unmeasured Confounding
by Zhengling Qi & Rui Miao & Xiaoke Zhang - 929-941 Finite-dimensional Discrete Random Structures and Bayesian Clustering
by Antonio Lijoi & Igor Prünster & Tommaso Rigon - 942-956 Partially Linear Additive Regression with a General Hilbertian Response
by Sungho Cho & Jeong Min Jeon & Dongwoo Kim & Kyusang Yu & Byeong U. Park - 957-969 Simultaneous Decorrelation of Matrix Time Series
by Yuefeng Han & Rong Chen & Cun-Hui Zhang & Qiwei Yao - 970-982 Adaptive Algorithm for Multi-Armed Bandit Problem with High-Dimensional Covariates
by Wei Qian & Ching-Kang Ing & Ji Liu - 983-994 Confidently Comparing Estimates with the c-value
by Brian L. Trippe & Sameer K. Deshpande & Tamara Broderick - 995-1007 Guaranteed Functional Tensor Singular Value Decomposition
by Rungang Han & Pixu Shi & Anru R. Zhang - 1008-1018 A Random Projection Approach to Hypothesis Tests in High-Dimensional Single-Index Models
by Changyu Liu & Xingqiu Zhao & Jian Huang - 1019-1031 Higher-Order Least Squares: Assessing Partial Goodness of Fit of Linear Causal Models
by Christoph Schultheiss & Peter Bühlmann & Ming Yuan - 1032-1043 On Semiparametrically Dynamic Functional-Coefficient Autoregressive Spatio-Temporal Models with Irregular Location Wide Nonstationarity
by Zudi Lu & Xiaohang Ren & Rongmao Zhang - 1044-1054 Copula Based Cox Proportional Hazards Models for Dependent Censoring
by Negera Wakgari Deresa & Ingrid Van Keilegom - 1055-1064 Optimal Linear Discriminant Analysis for High-Dimensional Functional Data
by Kaijie Xue & Jin Yang & Fang Yao - 1065-1075 A General M-estimation Theory in Semi-Supervised Framework
by Shanshan Song & Yuanyuan Lin & Yong Zhou - 1076-1088 Are Latent Factor Regression and Sparse Regression Adequate?
by Jianqing Fan & Zhipeng Lou & Mengxin Yu - 1089-1101 Variational Bayes for Fast and Accurate Empirical Likelihood Inference
by Weichang Yu & Howard D. Bondell - 1102-1111 Kernel Estimation of Bivariate Time-Varying Coefficient Model for Longitudinal Data with Terminal Event
by Yue Wang & Bin Nan & John D. Kalbfleisch - 1112-1123 Bayesian Robustness: A Nonasymptotic Viewpoint
by Kush Bhatia & Yi-An Ma & Anca D. Dragan & Peter L. Bartlett & Michael I. Jordan - 1124-1135 Skeleton Clustering: Dimension-Free Density-Aided Clustering
by Zeyu Wei & Yen-Chi Chen - 1136-1154 A Two-Sample Conditional Distribution Test Using Conformal Prediction and Weighted Rank Sum
by Xiaoyu Hu & Jing Lei - 1155-1167 Bayesian Modeling with Spatial Curvature Processes
by Aritra Halder & Sudipto Banerjee & Dipak K. Dey - 1168-1180 Solving Estimating Equations With Copulas
by Thomas Nagler & Thibault Vatter - 1181-1191 Intraday Periodic Volatility Curves
by Torben G. Andersen & Tao Su & Viktor Todorov & Zhiyuan Zhang - 1192-1204 Crowdsourcing Utilizing Subgroup Structure of Latent Factor Modeling
by Qi Xu & Yubai Yuan & Junhui Wang & Annie Qu - 1205-1214 Nonlinear Causal Discovery with Confounders
by Chunlin Li & Xiaotong Shen & Wei Pan - 1215-1228 Online Smooth Backfitting for Generalized Additive Models
by Ying Yang & Fang Yao & Peng Zhao - 1229-1239 Hypotheses Testing from Complex Survey Data Using Bootstrap Weights: A Unified Approach
by Jae Kwang Kim & J. N. K. Rao & Zhonglei Wang - 1240-1251 Instrumental Variable Estimation of Marginal Structural Mean Models for Time-Varying Treatment
by Haben Michael & Yifan Cui & Scott A. Lorch & Eric J. Tchetgen Tchetgen - 1252-1263 Factor Modeling for Clustering High-Dimensional Time Series
by Bo Zhang & Guangming Pan & Qiwei Yao & Wang Zhou - 1264-1273 Network Inference Using the Hub Model and Variants
by Zhibing He & Yunpeng Zhao & Peter Bickel & Charles Weko & Dan Cheng & Jirui Wang - 1274-1285 Estimation and Inference for High-Dimensional Generalized Linear Models with Knowledge Transfer
by Sai Li & Linjun Zhang & T. Tony Cai & Hongzhe Li - 1286-1296 On Learning and Testing of Counterfactual Fairness through Data Preprocessing
by Haoyu Chen & Wenbin Lu & Rui Song & Pulak Ghosh - 1297-1308 Distributed Inference for Spatial Extremes Modeling in High Dimensions
by Emily C. Hector & Brian J. Reich - 1309-1321 Doubly Robust Capture-Recapture Methods for Estimating Population Size
by Manjari Das & Edward H. Kennedy & Nicholas P. Jewell - 1322-1335 Variable Selection for High-Dimensional Nodal Attributes in Social Networks with Degree Heterogeneity
by Jia Wang & Xizhen Cai & Xiaoyue Niu & Runze Li - 1336-1347 Fixed-Domain Posterior Contraction Rates for Spatial Gaussian Process Model with Nugget
by Cheng Li & Saifei Sun & Yichen Zhu - 1348-1359 Semiparametric Proximal Causal Inference
by Yifan Cui & Hongming Pu & Xu Shi & Wang Miao & Eric Tchetgen Tchetgen - 1360-1373 Bayesian Conditional Transformation Models
by Manuel Carlan & Thomas Kneib & Nadja Klein - 1374-1384 Cohesion and Repulsion in Bayesian Distance Clustering
by Abhinav Natarajan & Maria De Iorio & Andreas Heinecke & Emanuel Mayer & Simon Glenn - 1385-1395 Feature Screening with Conditional Rank Utility for Big-Data Classification
by Xingxiang Li & Chen Xu - 1396-1408 Test of Significance for High-Dimensional Thresholds with Application to Individualized Minimal Clinically Important Difference
by Huijie Feng & Jingyi Duan & Yang Ning & Jiwei Zhao - 1409-1423 Scalable Bayesian Transport Maps for High-Dimensional Non-Gaussian Spatial Fields
by Matthias Katzfuss & Florian Schäfer - 1424-1433 Tail Spectral Density Estimation and Its Uncertainty Quantification: Another Look at Tail Dependent Time Series Analysis
by Ting Zhang & Beibei Xu - 1434-1445 Cross-Validation: What Does It Estimate and How Well Does It Do It?
by Stephen Bates & Trevor Hastie & Robert Tibshirani - 1446-1460 Efficient Multimodal Sampling via Tempered Distribution Flow
by Yixuan Qiu & Xiao Wang - 1461-1472 Inference in High-Dimensional Online Changepoint Detection
by Yudong Chen & Tengyao Wang & Richard J. Samworth - 1473-1485 Adaptive Functional Thresholding for Sparse Covariance Function Estimation in High Dimensions
by Qin Fang & Shaojun Guo & Xinghao Qiao - 1486-1499 Statistical Inferences for Complex Dependence of Multimodal Imaging Data
by Jinyuan Chang & Jing He & Jian Kang & Mingcong Wu - 1500-1512 Sparse Convoluted Rank Regression in High Dimensions
by Le Zhou & Boxiang Wang & Hui Zou - 1513-1525 Testing Simultaneous Diagonalizability
by Yuchen Xu & Marie-Christine Düker & David S. Matteson - 1526-1540 A Unified Inference for Predictive Quantile Regression
by Xiaohui Liu & Wei Long & Liang Peng & Bingduo Yang - 1541-1553 Inference for Treatment-Specific Survival Curves Using Machine Learning
by Ted Westling & Alex Luedtke & Peter B. Gilbert & Marco Carone - 1554-1565 Anytime-Valid Tests of Conditional Independence Under Model-X
by Peter Grünwald & Alexander Henzi & Tyron Lardy - 1566-1578 Ridge Regression Under Dense Factor Augmented Models
by Yi He - 1579-1591 Estimation of Linear Functionals in High-Dimensional Linear Models: From Sparsity to Nonsparsity
by Junlong Zhao & Yang Zhou & Yufeng Liu - 1592-1603 Censored Interquantile Regression Model with Time-Dependent Covariates
by Chi Wing Chu & Tony Sit - 1604-1618 Large-Scale Two-Sample Comparison of Support Sets
by Haoyu Geng & Xiaolong Cui & Haojie Ren & Changliang Zou - 1619-1632 A Hierarchical Expected Improvement Method for Bayesian Optimization
by Zhehui Chen & Simon Mak & C. F. Jeff Wu - 1633-1646 Narrowest Significance Pursuit: Inference for Multiple Change-Points in Linear Models
by Piotr Fryzlewicz - 1647-1656 Survival Mixed Membership Blockmodel
by Fangda Song & Jing Chu & Shuangge Ma & Yingying Wei - 1657-1670 Independence Weights for Causal Inference with Continuous Treatments
by Jared D. Huling & Noah Greifer & Guanhua Chen - 1671-1686 Markov Bases: A 25 Year Update
by Félix Almendra-Hernández & Jesús A. De Loera & Sonja Petrović - 1687-1689 Mathematical Foundations of Infinite-Dimensional Statistical Models
by Bodhisattva Sen - 1689-1690 Theory of Statistical Inference
by Somabha Mukherjee - 1690-1691 Quantitative Methods for Precision Medicine: Pharmacogenomics in Action
by Arthur Berg - 1691-1692 Statistical Modeling with R: A Dual Frequentist and Bayesian Approach for Life Scientists
by Christian P. Robert - 1692-1693 Data Science and Predictive Analytics, 2nd ed
by Xing Qiu - 1694-1695 Correction
by Pavel N. Krivitsky & Pietro Coletti & Niel Hens
January 2024, Volume 119, Issue 545
- 1-13 Overcoming Repeated Testing Schedule Bias in Estimates of Disease Prevalence
by Patrick M. Schnell & Matthew Wascher & Grzegorz A. Rempala - 14-26 Heterogeneous Distributed Lag Models to Estimate Personalized Effects of Maternal Exposures to Air Pollution
by Daniel Mork & Marianthi-Anna Kioumourtzoglou & Marc Weisskopf & Brent A. Coull & Ander Wilson - 27-38 A Semiparametric Inverse Reinforcement Learning Approach to Characterize Decision Making for Mental Disorders
by Xingche Guo & Donglin Zeng & Yuanjia Wang - 39-51 Hierarchical Neyman-Pearson Classification for Prioritizing Severe Disease Categories in COVID-19 Patient Data
by Lijia Wang & Y. X. Rachel Wang & Jingyi Jessica Li & Xin Tong - 52-65 A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses with Evaluations on Administrative and Survey Data
by Andrés F. Barrientos & Aaron R. Williams & Joshua Snoke & Claire McKay Bowen - 66-80 Bayesian Lesion Estimation with a Structured Spike-and-Slab Prior
by Anna Menacher & Thomas E. Nichols & Chris Holmes & Habib Ganjgahi - 81-94 Operator-Induced Structural Variable Selection for Identifying Materials Genes
by Shengbin Ye & Thomas P. Senftle & Meng Li - 95-108 Latent Network Structure Learning From High-Dimensional Multivariate Point Processes
by Biao Cai & Jingfei Zhang & Yongtao Guan - 109-121 Bayesian Markov-Switching Tensor Regression for Time-Varying Networks
by Monica Billio & Roberto Casarin & Matteo Iacopini - 122-135 Conformal Sensitivity Analysis for Individual Treatment Effects
by Mingzhang Yin & Claudia Shi & Yixin Wang & David M. Blei - 136-150 Randomization-based Joint Central Limit Theorem and Efficient Covariate Adjustment in Randomized Block 2K Factorial Experiments
by Hanzhong Liu & Jiyang Ren & Yuehan Yang - 151-162 A New and Unified Family of Covariate Adaptive Randomization Procedures and Their Properties
by Wei Ma & Ping Li & Li-Xin Zhang & Feifang Hu - 163-175 Heavy-Tailed Density Estimation
by Surya T. Tokdar & Sheng Jiang & Erika L. Cunningham - 176-188 Nonparametric Estimation of Repeated Densities with Heterogeneous Sample Sizes
by Jiaming Qiu & Xiongtao Dai & Zhengyuan Zhu - 189-201 Hidden Markov Pólya Trees for High-Dimensional Distributions
by Naoki Awaya & Li Ma - 202-216 Low-Rank Regression Models for Multiple Binary Responses and their Applications to Cancer Cell-Line Encyclopedia Data
by Seyoung Park & Eun Ryung Lee & Hongyu Zhao - 217-231 Bias-Correction and Test for Mark-Point Dependence with Replicated Marked Point Processes
by Ganggang Xu & Jingfei Zhang & Yehua Li & Yongtao Guan - 232-245 Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons
by Chengchun Shi & Shikai Luo & Yuan Le & Hongtu Zhu & Rui Song - 246-258 Nearly Dimension-Independent Sparse Linear Bandit over Small Action Spaces via Best Subset Selection
by Yi Chen & Yining Wang & Ethan X. Fang & Zhaoran Wang & Runze Li - 259-272 An Empirical Bayes Approach to Shrinkage Estimation on the Manifold of Symmetric Positive-Definite Matrices
by Chun-Hao Yang & Hani Doss & Baba C. Vemuri - 273-284 Off-Policy Confidence Interval Estimation with Confounded Markov Decision Process
by Chengchun Shi & Jin Zhu & Shen Ye & Shikai Luo & Hongtu Zhu & Rui Song - 285-296 Optimal One-Pass Nonparametric Estimation Under Memory Constraint
by Mingxue Quan & Zhenhua Lin - 297-307 Optimal Nonparametric Inference with Two-Scale Distributional Nearest Neighbors
by Emre Demirkaya & Yingying Fan & Lan Gao & Jinchi Lv & Patrick Vossler & Jingbo Wang - 308-319 Dynamic Principal Component Analysis in High Dimensions
by Xiaoyu Hu & Fang Yao - 320-331 Scaled Process Priors for Bayesian Nonparametric Estimation of the Unseen Genetic Variation
by Federico Camerlenghi & Stefano Favaro & Lorenzo Masoero & Tamara Broderick - 332-342 Selective Inference for Hierarchical Clustering
by Lucy L. Gao & Jacob Bien & Daniela Witten - 343-355 Subspace Estimation with Automatic Dimension and Variable Selection in Sufficient Dimension Reduction
by Jing Zeng & Qing Mai & Xin Zhang - 356-367 Fast and Numerically Stable Particle-Based Online Additive Smoothing: The AdaSmooth Algorithm
by Alessandro Mastrototaro & Jimmy Olsson & Johan Alenlöv - 368-381 An Additive Graphical Model for Discrete Data
by Jun Tao & Bing Li & Lingzhou Xue - 382-393 Bootstrapping Extreme Value Estimators
by Laurens de Haan & Chen Zhou - 394-406 Fisher-Pitman Permutation Tests Based on Nonparametric Poisson Mixtures with Application to Single Cell Genomics
by Zhen Miao & Weihao Kong & Ramya Korlakai Vinayak & Wei Sun & Fang Han - 407-421 Modeling and Active Learning for Experiments with Quantitative-Sequence Factors
by Qian Xiao & Yaping Wang & Abhyuday Mandal & Xinwei Deng - 422-433 Bayesian Spatial Blind Source Separation via the Thresholded Gaussian Process
by Ben Wu & Ying Guo & Jian Kang - 434-449 Using SVD for Topic Modeling
by Zheng Tracy Ke & Minzhe Wang - 450-460 To Adjust or not to Adjust? Estimating the Average Treatment Effect in Randomized Experiments with Missing Covariates
by Anqi Zhao & Peng Ding - 461-474 Anomaly Detection for a Large Number of Streams: A Permutation-Based Higher Criticism Approach
by Ivo V. Stoepker & Rui M. Castro & Ery Arias-Castro & Edwin van den Heuvel - 475-484 Assumption-Lean Cox Regression
by Stijn Vansteelandt & Oliver Dukes & Kelly Van Lancker & Torben Martinussen - 485-497 Learning Coefficient Heterogeneity over Networks: A Distributed Spanning-Tree-Based Fused-Lasso Regression
by Xin Zhang & Jia Liu & Zhengyuan Zhu - 498-510 An Algebraic Estimator for Large Spectral Density Matrices
by Matteo Barigozzi & Matteo Farnè - 511-524 Fisher’s Combined Probability Test for High-Dimensional Covariance Matrices
by Xiufan Yu & Danning Li & Lingzhou Xue - 525-537 Large Scale Prediction with Decision Trees
by Jason M. Klusowski & Peter M. Tian - 538-551 Distribution of Distances based Object Matching: Asymptotic Inference
by Christoph Alexander Weitkamp & Katharina Proksch & Carla Tameling & Axel Munk - 552-564 Policy Optimization Using Semiparametric Models for Dynamic Pricing
by Jianqing Fan & Yongyi Guo & Mengxin Yu - 565-581 Inference in Heavy-Tailed Nonstationary Multivariate Time Series
by Matteo Barigozzi & Giuseppe Cavaliere & Lorenzo Trapani - 582-596 A Mass-Shifting Phenomenon of Truncated Multivariate Normal Priors
by Shuang Zhou & Pallavi Ray & Debdeep Pati & Anirban Bhattacharya - 597-611 Causal Inference for Social Network Data
by Elizabeth L. Ogburn & Oleg Sofrygin & Iván Díaz & Mark J. van der Laan - 612-624 Estimating the Spectral Density at Frequencies Near Zero
by Tucker McElroy & Dimitris N. Politis - 625-638 Estimating Optimal Infinite Horizon Dynamic Treatment Regimes via pT-Learning
by Wenzhuo Zhou & Ruoqing Zhu & Annie Qu - 639-649 Statistical Learning for Individualized Asset Allocation
by Yi Ding & Yingying Li & Rui Song - 650-663 Multi-Task Learning with High-Dimensional Noisy Images
by Xin Ma & Suprateek Kundu - 664-677 Modeling Point Referenced Spatial Count Data: A Poisson Process Approach
by Diego Morales-Navarrete & Moreno Bevilacqua & Christian Caamaño-Carrillo & Luis M. Castro - 678-689 Robust Inference and Modeling of Mean and Dispersion for Generalized Linear Models
by Jolien Ponnet & Pieter Segaert & Stefan Van Aelst & Tim Verdonck - 690-700 Stochastic Convergence Rates and Applications of Adaptive Quadrature in Bayesian Inference
by Blair Bilodeau & Alex Stringer & Yanbo Tang - 701-714 Nonparametric Two-Sample Tests of High Dimensional Mean Vectors via Random Integration
by Yunlu Jiang & Xueqin Wang & Canhong Wen & Yukang Jiang & Heping Zhang - 715-729 Robust High-Dimensional Regression with Coefficient Thresholding and Its Application to Imaging Data Analysis
by Bingyuan Liu & Qi Zhang & Lingzhou Xue & Peter X.-K. Song & Jian Kang - 730-743 Fair Policy Targeting
by Davide Viviano & Jelena Bradic - 744-756 Projection Test for Mean Vector in High Dimensions
by Wanjun Liu & Xiufan Yu & Wei Zhong & Runze Li - 757-772 Matching on Generalized Propensity Scores with Continuous Exposures
by Xiao Wu & Fabrizia Mealli & Marianthi-Anna Kioumourtzoglou & Francesca Dominici & Danielle Braun - 773-785 Recommender Systems: A Review
by Patrick M. LeBlanc & David Banks & Linhui Fu & Mingyan Li & Zhengyu Tang & Qiuyi Wu - 786-787 Statistical Analytics for Health Data Science with SAS and R
by Ali Rahnavard - 787-789 Martingale Methods in Statistics
by Insuk Seo - 789-790 Stable Lévy Processes via Lamperti-Type Representations
by Giacomo Bormetti - 790-791 Fundamentals of Causal Inference: With R
by Ting Ye - 791-791 Handbook of Matching and Weighting Adjustments for Causal Inference
by Raymond K. W. Wong - 792-793 The Journal of the American Statistical Association 2023 Associate Editors
by The Editors
October 2023, Volume 118, Issue 544
- 2213-2224 A Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks
by Pavel N. Krivitsky & Pietro Coletti & Niel Hens - 2225-2227 Discussion of “A Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks” by Pavel N. Krivitsky, Pietro Coletti, and Niel Hens
by Michael Schweinberger & Cornelius Fritz - 2228-2231 Power and Multicollinearity in Small Networks: A Discussion of “Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks” by Krivitsky, Coletti, and Hens
by George G. Vega Yon - 2232-2234 Discussion of “A Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks”
by Nynke M. D. Niezink - 2235-2238 Rejoinder to Discussion of “A Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks”
by Pavel N. Krivitsky & Pietro Coletti & Niel Hens - 2239-2249 Modeling Postoperative Mortality in Older Patients by Boosting Discrete-Time Competing Risks Models
by Moritz Berger & Ana Kowark & Rolf Rossaint & Mark Coburn & Matthias Schmid - 2250-2261 Covariate-Informed Latent Interaction Models: Addressing Geographic & Taxonomic Bias in Predicting Bird–Plant Interactions
by Georgia Papadogeorgou & Carolina Bello & Otso Ovaskainen & David B. Dunson - 2262-2275 Analyzing Big EHR Data—Optimal Cox Regression Subsampling Procedure with Rare Events
by Nir Keret & Malka Gorfine - 2276-2287 Accommodating Time-Varying Heterogeneity in Risk Estimation under the Cox Model: A Transfer Learning Approach
by Ziyi Li & Yu Shen & Jing Ning - 2288-2300 Mixed-Response State-Space Model for Analyzing Multi-Dimensional Digital Phenotypes
by Tianchen Xu & Yuan Chen & Donglin Zeng & Yuanjia Wang - 2301-2314 Bayesian Nonparametric Common Atoms Regression for Generating Synthetic Controls in Clinical Trials
by Noirrit Kiran Chandra & Abhra Sarkar & John F. de Groot & Ying Yuan & Peter Müller - 2315-2328 Understanding Implicit Regularization in Over-Parameterized Single Index Model
by Jianqing Fan & Zhuoran Yang & Mengxin Yu - 2329-2343 Coordinatewise Gaussianization: Theories and Applications
by Qing Mai & Di He & Hui Zou - 2344-2355 Marginal and Conditional Multiple Inference for Linear Mixed Model Predictors
by Peter Kramlinger & Tatyana Krivobokova & Stefan Sperlich - 2356-2369 A Zero-Inflated Logistic Normal Multinomial Model for Extracting Microbial Compositions
by Yanyan Zeng & Daolin Pang & Hongyu Zhao & Tao Wang - 2370-2382 Toward Better Practice of Covariate Adjustment in Analyzing Randomized Clinical Trials
by Ting Ye & Jun Shao & Yanyao Yi & Qingyuan Zhao - 2383-2393 Sparse Reduced Rank Huber Regression in High Dimensions
by Kean Ming Tan & Qiang Sun & Daniela Witten - 2394-2405 Robust Estimation of Large Panels with Factor Structures
by Marco Avarucci & Paolo Zaffaroni - 2406-2421 Survival Analysis via Ordinary Differential Equations
by Weijing Tang & Kevin He & Gongjun Xu & Ji Zhu - 2422-2432 A General Pairwise Comparison Model for Extremely Sparse Networks
by Ruijian Han & Yiming Xu & Kani Chen - 2433-2445 Bias-Adjusted Spectral Clustering in Multi-Layer Stochastic Block Models
by Jing Lei & Kevin Z. Lin - 2446-2453 Sharp Nonparametric Bounds for Decomposition Effects with Two Binary Mediators
by Erin E. Gabriel & Michael C. Sachs & Arvid Sjölander - 2454-2467 Self-supervised Metric Learning in Multi-View Data: A Downstream Task Perspective
by Shulei Wang - 2468-2481 Prior-Preconditioned Conjugate Gradient Method for Accelerated Gibbs Sampling in “Large n, Large p” Bayesian Sparse Regression
by Akihiko Nishimura & Marc A. Suchard - 2482-2490 Efficient Estimation in the Fine and Gray Model
by Thomas H. Scheike & Torben Martinussen & Brice Ozenne - 2491-2502 Distribution-Free Prediction Sets for Two-Layer Hierarchical Models
by Robin Dunn & Larry Wasserman & Aaditya Ramdas - 2503-2520 False Discovery Rate Control via Data Splitting
by Chenguang Dai & Buyu Lin & Xin Xing & Jun S. Liu - 2521-2532 Bayesian Modeling of Sequential Discoveries
by Alessandro Zito & Tommaso Rigon & Otso Ovaskainen & David B. Dunson - 2533-2547 Metropolis–Hastings via Classification
by Tetsuya Kaji & Veronika Ročková - 2548-2561 Power-Enhanced Simultaneous Test of High-Dimensional Mean Vectors and Covariance Matrices with Application to Gene-Set Testing
by Xiufan Yu & Danning Li & Lingzhou Xue & Runze Li - 2562-2574 Random Surface Covariance Estimation by Shifted Partial Tracing
by Tomas Masak & Victor M. Panaretos - 2575-2587 Model-Free Conditional Feature Screening with FDR Control
by Zhaoxue Tong & Zhanrui Cai & Songshan Yang & Runze Li - 2588-2604 Generalized Low-Rank Plus Sparse Tensor Estimation by Fast Riemannian Optimization
by Jian-Feng Cai & Jingyang Li & Dong Xia - 2605-2619 Covariate-Assisted Sparse Tensor Completion
by Hilda S. Ibriga & Will Wei Sun - 2620-2631 Covariance Estimation for Matrix-valued Data
by Yichi Zhang & Weining Shen & Dehan Kong - 2632-2644 Transformation-Invariant Learning of Optimal Individualized Decision Rules with Time-to-Event Outcomes
by Yu Zhou & Lan Wang & Rui Song & Tuoyi Zhao - 2645-2657 Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile Balancing
by Jacob Dorn & Kevin Guo - 2658-2670 Rank-Based Greedy Model Averaging for High-Dimensional Survival Data
by Baihua He & Shuangge Ma & Xinyu Zhang & Li-Xing Zhu - 2671-2683 Conditional Separable Effects
by Mats J. Stensrud & James M. Robins & Aaron Sarvet & Eric J. Tchetgen Tchetgen & Jessica G. Young - 2684-2697 Transfer Learning Under High-Dimensional Generalized Linear Models
by Ye Tian & Yang Feng - 2698-2711 Divide-and-Conquer: A Distributed Hierarchical Factor Approach to Modeling Large-Scale Time Series Data
by Zhaoxing Gao & Ruey S. Tsay - 2712-2720 The Maximum of the Periodogram of a Sequence of Functional Data
by Clément Cerovecki & Vaidotas Characiejus & Siegfried Hörmann - 2721-2735 Inference for Local Parameters in Convexity Constrained Models
by Hang Deng & Qiyang Han & Bodhisattva Sen - 2736-2745 A Bayesian Approach to Multiple-Output Quantile Regression
by Michael Guggisberg - 2746-2761 Spatio-Temporal Cross-Covariance Functions under the Lagrangian Framework with Multiple Advections
by Mary Lai O. Salvaña & Amanda Lenzi & Marc G. Genton - 2762-2775 Efficient Estimation for Censored Quantile Regression
by Sze Ming Lee & Tony Sit & Gongjun Xu - 2776-2792 Multiple Change Point Detection in Reduced Rank High Dimensional Vector Autoregressive Models
by Peiliang Bai & Abolfazl Safikhani & George Michailidis - 2793-2809 Improved Small Domain Estimation via Compromise Regression Weights
by Nicholas C. Henderson & Ravi Varadhan & Thomas A. Louis - 2810-2820 Approximate Selective Inference via Maximum Likelihood
by Snigdha Panigrahi & Jonathan Taylor - 2821-2832 Bayesian Inference Using Synthetic Likelihood: Asymptotics and Adjustments
by David T. Frazier & David J. Nott & Christopher Drovandi & Robert Kohn - 2833-2846 Permutation Tests at Nonparametric Rates
by Marinho Bertanha & Eunyi Chung - 2847-2859 Set-Valued Support Vector Machine with Bounded Error Rates
by Wenbo Wang & Xingye Qiao - 2860-2875 Learning Topic Models: Identifiability and Finite-Sample Analysis
by Yinyin Chen & Shishuang He & Yun Yang & Feng Liang - 2876-2888 Benign Overfitting and Noisy Features
by Zhu Li & Weijie J. Su & Dino Sejdinovic - 2889-2900 Hypothesis Tests for Structured Rank Correlation Matrices
by Samuel Perreault & Johanna G. Nešlehová & Thierry Duchesne - 2901-2914 Online Bootstrap Inference For Policy Evaluation In Reinforcement Learning
by Pratik Ramprasad & Yuantong Li & Zhuoran Yang & Zhaoran Wang & Will Wei Sun & Guang Cheng - 2915-2927 Reversible Jump PDMP Samplers for Variable Selection
by Augustin Chevallier & Paul Fearnhead & Matthew Sutton - 2928-2942 What is a Randomization Test?
by Yao Zhang & Qingyuan Zhao - 2943-2945 Bayesian Filtering and Smoothing, 2nd ed
by Jaewoo Park - 2945-2945 Confidence Intervals for Discrete Data in Clinical Research
by Alan Agresti
July 2023, Volume 118, Issue 543
- 1473-1487 Genetic Underpinnings of Brain Structural Connectome for Young Adults
by Yize Zhao & Changgee Chang & Jingwen Zhang & Zhengwu Zhang - 1488-1499 Assessing the Most Vulnerable Subgroup to Type II Diabetes Associated with Statin Usage: Evidence from Electronic Health Record Data
by Xinzhou Guo & Waverly Wei & Molei Liu & Tianxi Cai & Chong Wu & Jingshen Wang - 1500-1514 Compositional Graphical Lasso Resolves the Impact of Parasitic Infection on Gut Microbial Interaction Networks in a Zebrafish Model
by Chuan Tian & Duo Jiang & Austin Hammer & Thomas Sharpton & Yuan Jiang