Papers to Appear in Subsequent Issues

Testability of High-Dimensional Linear Models with Non-Sparse Structures Jelena Bradic, Jianqing Fan, and Yinchu Zhu
Adaptive Estimation of Multivariate Regression with Hidden Variables Xin Bing
An Optimal Statistical and Computational Framework for Generalized Tensor Estimation Rungang Han, Rebecca Willett, and Anru Zhang
Spatial dependence and space-time trend in extreme events John Einmahl, Ana Ferreira, Laurens de Haan, Claudia Neves, and Chen Zhou
Heteroskedastic PCA: Algorithm, Optimality, and Applications Anru Zhang, T. Tony Cai, and Yihong Wu
Community Detection on Mixture Multi-Layer Networks Via Regularized Tensor Decomposition Bing-Yi Jing, Ting Li, Zhongyuan Lyu, and Dong Xia
On Minimax Optimality of Sparse Bayes Predictive Density Estimates Gourab Mukherjee and Iain M Johnstone
Dimension reduction for functional data based on weak conditional moments Bing Li and Jun Song
Pattern Graphs: a Graphical Approach to Nonmonotone Missing Data Yen-Chi Chen
Testing Community Structure for Hypergraphs Mingao Yuan, Ruiqi Liu, Yang Feng, and Zuofeng Shang
Fundamental Barriers to High-Dimensional Regression with Convex Penalties Michael V Celentano and Andrea Montanari
Approximate Message Passing algorithms for rotationally invariant matrices Zhou Fan
Minimax optimality of permutation tests Ilmun Kim, Sivaraman Balakrishnan, and Larry Wasserman
Powerful Knockoffs via Minimizing Reconstructability Asher Spector and Lucas Janson
On Least Squares Estimation Under Heteroscedastic and Heavy-Tailed Errors Arun K Kuchibhotla and Rohit K Patra
Deconvolution with unknown noise distribution is possible for multivariate signals Elisabeth Gassiat, Sylvain Le Corff, and Luc Lehéricy
Isotonic regression with unknown permutations: Statistics, computation, and adaptation Ashwin Pananjady and Richard J. Samworth
Admissible ways of merging p-values under arbitrary dependence Vladimir Vovk, Bin Wang, and Ruodu Wang
High Dimensional Asymptotics of Likelihood Ratio Tests in Gaussian Sequence Model Under Convex Constraint Qiyang Han, Bodhisattva Sen, and Yandi Shen
Testing Equivalence of Clustering Chao Gao and Zongming Ma
Continuous-time targeted minimum loss-based estimation of intervention-specific mean outcomes Helene Charlotte Rytgaard, Thomas A. Gerds, and Mark J. van der Laan
Sharp minimax nonparametric estimation of pure quantum states Samriddha Lahiry and Michael Nussbaum
Canonical thresholding for non-sparse high dimensional linear regression Igor Silin and Jianqing Fan
Semiparametric latent-class models for multivariate longitudinal and survival data Kin Yau Wong, Donglin Zeng, and Dan-Yu Lin
Robust subgaussian estimation of a mean vector in nearly linear time Jules Depersin and Guillaume Lecué
On an Extenstion of the Promotion Time Cure Model Jad Beyhum, François Portier, Ingrid Van Keilegom, and Anouar El Ghouch
Convergence of de Finetti’s mixing measure in latent structure models for observed exchangeable sequences Yun Wei and XuanLong Nguyen
Backfitting for large scale crossed random effects regressions Trevor Hastie, Swarnadip Ghosh, and Art B Owen
Refined Cramér Type Moderate Deviation Theorems for General Self-normalized Sums with Applications to Dependent Random Variables and Winsorized Mean Lan Gao, Qi-Man Shao, and Jiasheng Shi
Tensor Clustering with Planted Structures: Statistical Optimality and Computational Limits Yuetian Luo and Anru R Zhang
Distributed Nonparametric Regression: Optimal Rate of Convergence and Cost of Adaptation Tony Cai and Hongji Wei
Edgeworth expansions for network moments Yuan Zhang and Dong Xia
Parametric copula adjusted for non- and semi-parametric regression Yue Zhao, Irène Gijbels, and Ingrid Van Keilegom
Inference for change-points in high-dimensional data via self-normalization Xiaofeng Shao, Runmin Wang, Changbo Zhu, and Stanislav Volgushev
Optimal False Discovery Rate Control for Large Scale Multiple Testing with Auxiliary Information Hongyuan Cao, Jun Chen, and Xianyang Zhang
Adaptive test of independence based on HSIC measures Beatrice Laurent, Melisande Albert, Amandine Marrel, and Anouar Meynaoui
Sparse High-Dimensional Linear Regression. Algorithmic Barriers and a Local Search Algorithm David Gamarnik and Ilias Zadik
Functional Sufficient Dimension Reduction through Average Frechet Derivatives Kuang-Yao Lee and Lexin Li
General and Feasible Tests with Multiply-Imputed Datasets Kin Wai Chan
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie, Andrea Montanari, Saharon Rosset, and Ryan Joseph Tibshirani
Motif Estimation via Subgraph Sampling: The Fourth Moment Phenomenon Bhaswar B. Bhattacharya, Sayan Das, and Sumit Mukherjee
Correction to: Asymptotic genealogies of interacting particle systems with an application to sequential Monte Carlo Jere Koskela, Paul A Jenkins, Adam M Johansen, and Dario Spano
Multivariate Ranks and Quantiles using Optimal Transport: Consistency, Rates, and Nonparametric Testing Promit Ghosal and Bodhisattva Sen
Conditional Calibration for False Discovery Rate Control Under Dependence William Fithian and Lihua Lei
Necessary and sufficient conditions for asymptotically optimal linear prediction of random fields on compact metric spaces Kristin Kirchner and David Bolin
Detecting Multiple Replicating Signals using Adaptive Filtering Procedures Jingshu Wang, Lin Gui, Weijie J. Su, Chiara Sabatti, and Art B. Owen
Iterative Algorithm for Discrete Structure Recovery Chao Gao and Anderson Zhang
False discovery rate control with unknown null distribution: is it possible to mimic the oracle? Etienne Roquain and Verzelen Nicolas
Max-Sum tests for cross-sectional independence of high-dimensional panel data Long Feng, Tiefeng Jiang, Binghui Liu and Wei Xiong
Statistical inference for principal components of spiked covariance matrices Zhigang Bao, Xiucai Ding, Jingming Wang, and Ke Wang
Reconciling design-based and model-based causal inferences for split-plot experiments Peng Ding
All-in-one robust estimator of the Gaussian mean Arnak Dalalyan and Arshak Minasyan
Inference for Low-rank Tensors — No Need to Debias Dong Xia, Anru Zhang, and Yuchen Zhou
Design admissibility and de la Garza phenomenon in multi-factor experiments Holger Dette, Xin Liu, and Rong-Xian Yue
Evidence Factors from Multiple, Possibly Invalid, Instrumental Variables Anqi Zhao, Youjin Lee, Dylan S Small, and Bikram Karmakar
Consistent Order Selection for ARFIMA Processes Hsueh-Han Huang, Ngai Hang Chan, Kun Chen, and Ching-Kang Ing
Optimal signal detection in some spiked random matrix models: likelihood ratio tests and linear spectral statistics Debapratim Banerjee and Zongming Ma
On universally consistent and fully distribution-free rank tests of vector independence Hongjian Shi, Marc Hallin, Mathias Drton, and Fang Han
Doubly Debiased Lasso: High-Dimensional Inference under Hidden Confounding Zijian Guo, Domagoj Ćevid, and Peter Bühlmann
Deep Learning for the Partially Linear Cox Model Qixian Zhong, Jonas Mueller, and Jane-Ling Wang
A General Framework: Optimal Difference-based Variance Estimator in Time Series Kin Wai Chan
Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives Hussein Hazimeh, Rahul Mazumder, and Peter Radchenko
Ridge Regression Revisited: Debiasing, Thresholding and Bootstrap Yunyi Zhang and Dimitris Politis
Cube Root Weak Convergence of Empirical Estimators of a Density Level Set Philippe Berthet and John H.J. Einmahl
Two-sample Testing for High-Dimensional Multinomials under Rare/Weak Perturbations David Leigh Donoho and Alon Kipnis
A New and Flexible Design Construction for Orthogonal Arrays and their Generalizations for Modern Applications Yuanzhen He, Chunfang Devon Lin, and Fasheng Sun
Consistency of Bayesian inference for multivariate max-stable distributions Simone Andrea Padoan and Stefano Rizzelli
Minimax estimation of smooth densities in Wasserstein distance Jonathan Niles-Weed and Quentin Berthet
Large scale inference with block structure Guenther Walther and Jiyao Kou
Uniform convergence of local Fréchet regression, with applications to locating extrema and time warping for metric space valued trajectories Yaqing Chen and Hans-Georg Müller
Cointegration in large VARs Anna Bykhovskaya and Vadim Gorin
Limit theorems for invariant distributions Morgane Austern and Peter Orbanz
Partial Recovery for Top-k Ranking: Optimality of MLE and Sub-Optimality of Spectral Method Pinhan Chen, Chao Gao, and Anderson Zhang
Distributed Adaptive Gaussian Mean Estimation with Unknown Variance: Interactive Protocol Helps Adaptation Tony Cai and Hongji Wei
A data-adaptive method for estimating density level sets under shape conditions Alberto Rodríguez-Casal and Paula Saavedra-Nieves
Asymptotic accuracy of the saddlepoint approximation for maximum likelihood estimation Jesse Goodman
A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-ℓ1-Norm Interpolated Classifiers Tengyuan Liang and Pragya Sur
Generalization Error Bounds of Dynamic Treatment Regimes in Regression-Based Learning Eun Jeong Oh, Min Qian, and Ken Cheung
Intrinsic Riemannian Functional Data Analysis for Sparse Longitudinal Observations Lingxuan Shao, Zhenhua Lin, and Fang Yao
Strong mixing condition for Hawkes processes and application to Whittle estimation from count data Felix Cheysson and Gabriel Lang
Model selection in the space of Gaussian models invariant by symmetry Piotr Graczyk, Hideyuki Ishi, Bartosz Kołodziejek, and Helene Massam
Optimal Full Ranking from Pairwise Comparisons Pinhan Chen, Chao Gao, and Anderson Ye Zhang