Papers to Appear in Subsequent Issues

When papers are accepted for publication, they will appear below. Any changes that are made during the production process will only appear in the final version. Papers listed here are not updated during the production process and are removed once an issue is published.

Wald Tests When Restrictions Are Locally Singular Jean-Marie Dufour, Eric Renault, and Victoria Zinde-Walsh
Large Dimensional Independent Component Analysis: Statistical Optimality and Computational Tractability Arnab Auddy and Ming Yuan
A Common-Cause Principle for Eliminating Selection Bias in Causal Estimands Through Covariate Adjustment Maya Mathur, Ilya Shpitser, and Tyler VanderWeele
Near-Optimal Inference in Adaptive Linear Regression Koulik Khamaru, Yash Deshpande, Tor Lattimore, Lester Mackey, and Martin J. Wainwright
Forward Selection and Post-Selection Inference in Factorial Designs Lei Shi, Jingshen Wang, and Peng Ding
Asymptotic Distributions of Largest Pearson Correlation Coefficients under Dependent Structures Tiefeng Jiang and Tuan Pham
Observable Adjustments in Single-Index Models for Regularized M-Estimators With Bounded p/n Pierre C. Bellec
Statistical Framework for Analyzing Shape in a Time Series of Random Geometric Objects Anne Margrete Nicolien van Delft and Andrew J. Blumberg
Approximation Error from  Discretizations and Its Applications Junlong Zhao, Xiumin Liu, Bin Du, and Yufeng Liu
Embedding Distributional Data Ery Arias-Castro and Wanli Qiao
Entropic Covariance Models Piotr Zwiernik
A New Central Limit Theorem for the Augmented IPW Estimator: Variance Inflation, Cross-fit Covariance and Beyond Kuanhao Jiang, Rajarshi Mukherjee, Subhabrata Sen, and Pragya Sur
Sparse Anomaly Detection Across Referentials: A Rank-Based Higher Criticism Approach Ivo V. Stoepker, Rui M. Castro, and Ery Arias-Castro
Studentized Tests of Independence: Random-Lifter Approach Gao Zhe, Roulin Wang, Xueqin Wang, and Heping Zhang
Residual Permutation Test for Regression Coefficient Testing Kaiyue Wen, Tengyao Wang, and Yuhao Wang
ARK: Robust Knockoffs Inference with Coupling Yingying Fan, Lan Gao, and Jinchi Lv
On the Convergence of Coordinate Ascent Variational Inference Anirban Bhattacharya, Debdeep Pati, and Yun Yang
Optimal Transport Map Estimation in General Function Spaces Vincent Divol, Jonathan Niles-Weed, and Aram-Alexandre Pooladian
Low Coordinate Degree Algorithms I: Universality of Computational Thresholds for Hypothesis Testing Dmitriy Kunisky
Semi-Parametric Inference Based on Adaptively Collected Data Licong Lin, Koulik Khamaru, and Martin J. Wainwright
Deep Approximate Policy Iteration Jin Liu
The Numeraire E-Variable and Reverse Information Projection Martin Larsson, Aaditya Ramdas, and Johannes Ruf
Asymptotically-Exact Selective Inference for Quantile Regression Yumeng Wang, Snigdha Panigrahi, and Xuming He
The Generalization Error of Max-Margin Linear Classifiers: Benign Overfitting and High Dimensional Asymptotics in the Overparametrized Regime Andrea Montanari, Feng Ruan, Youngtak Sohn, and Jun Yan
Precise Error Rates for Computationally Efficient Testing Ankur Moitra and Alexander S. Wein
A Unifying Framework for Global Gaussianization: Asymptotic Equivalence of Locally Stationary Processes and Bivariate White Noise Cristina Butucea, Alexander Meister, and Angelika Rohde
A Duality Framework for Analyzing Random Feature and Two-Layer Neural Networks Hongrui Chen, Jihao Long, and Lei Wu
BELIEF in Dependence: Leveraging Atomic Linearity in Data Bits for Rethinking Generalized Linear Models Benjamin Brown, Kai Zhang, and Xiao-Li Meng
Sparsity Meets Correlation in Gaussian Sequence Model Subhodh Kotekal and Chao Gao
Conformal Inference for Random Objects Hang Zhou and Hans-Georg Müller
Statistical Algorithms for Low-Frequency Diffusion Data: A PDE Approach Matteo Giordano and Sven Wang
Minimax Rate for Multivariate Data Under Componentwise Local Differential Privacy Constraints Chiara Amorino and Arnaud Gloter
Dualizing Le Cam’s Method for Functional Estimation, With Applications to Estimating the Unseens Yury Polyanskiy and Yihong Wu
Erratum: Quantile Processes and Their Applications in Finite Populations Anurag Dey and Probal Chaudhuri
Strong Approximations for Empirical Processes Indexed by Lipschitz Functions Ruiqi (Rae) Yu and Matias D. Cattaneo
Testing Stationarity and Change Point Detection in Reinforcement Learning Mengbing Li, Chengchun Shi, Zhenke Wu, and Piotr Fryzlewicz
Adaptive Estimation of the 𝕃2-Norm of a Probability Density and Related Topics I. Lower Bounds. Galatia Cleanthous, Athanasios Georgiadis, and Oleg Lepski
Adaptive Estimation of the 𝕃2-Norm of a Probability Density and Related Topics II. Upper Bounds via the Oracle Approach. Galatia Cleanthous, Athanasios Georgiadis, and Oleg Lepski
Asymptotic Distribution of Maximum Likelihood Estimator in Generalized Linear Mixed Models with Crossed Random Effects Jiming Jiang
On the Structural Dimension of Sliced Inverse Regression Dongming Huang, Songtao Tian, and Qian Lin
Semiparametric Modeling and Analysis for Longitudinal Network Data Yinqiu He, Jiajin Sun, Yuang Tian, Zhiliang Ying, and Yang Feng
Self-Normalized Cramér Type Moderate Deviation Theorem for Gaussian Approximation Jingkun Qiu, Song Xi Chen, and Qi-Man Shao
On the Multiway Principal Component Analysis Jialin Ouyang and Ming Yuan
Semiparametric Adaptive Estimation Under Informative Sampling Kosuke Morikawa, Yoshikazu Terada, and Jae Kwang Kim
Algorithmic Stability Implies Training-Conditional Coverage for Distribution-Free Prediction Methods Ruiting Liang and Rina Foygel Barber
Policy Learning “Without” Overlap: Pessimism and Generalized Empirical Bernstein’s Inequality Ying Jin, Zhimei Ren, Zhuoran Yang, and Zhaoran Wang
Reinforcement Learning for Individual Optimal Policy From Heterogeneous Data Rui Miao, Babak Shahbaba, and Annie Qu
Debiased Regression Adjustment in Completely Randomized Experiments With Moderately High-Dimensional Covariates Xin Lu, Fan Yang, and Yuhao Wang
Asymptotic Theory of Geometric and Adaptive k-Means Clustering Adam Quinn Jaffe
Fixed and Random Covariance Regression Analyses Tao Zou, Wei Lan, Runze Li, and Chih-Ling Tsai
Spectral Gap Bounds for Reversible Hybrid Gibbs Chains Qian Qin, Nianqiao Ju, and Guanyang Wang
Low-Degree Hardness of Detection for Correlated Erdős-Rényi Graphs Jian Ding, Hang Du, and Zhangsong Li
Optimal Vintage Factor Analysis With Deflation Varimax Xin Bing, Dian Jin, and Yuqian Zhang