Papers to Appear in Subsequent Issues

Testability of High-Dimensional Linear Models with Non-Sparse Structures Jelena Bradic, Jianqing Fan, and Yinchu Zhu
Optimal rates for independence testing via U-statistic permutation tests Thomas Berrett, Ioannis Kontoyiannis, and Richard John Samworth
Variable Selection Consistency of Gaussian Process Regression Sheng Jiang
Optimality of Spectral Clustering in the Gaussian Mixture Model Matthias Löffler, Anderson Ye Zhang, Harrison H. Zhou
Adaptive Estimation of Multivariate Piecewise Polynomials and Bounded Variation Functions by Optimal Decision Trees Sabyasachi Chatterjee and Subhajit Goswami
Rank-based Estimation under Asymptotic Dependence and Independence, with Applications to Spatial Extremes Michaël Lalancette, Sebastian Engelke, and Stanislav Volgushev
Estimation of Smooth Functionals in Normal Models: Bias Reduction and Asymptotic Efficiency Vladimir Koltchinskii and Mayya Zhilova
Additive Regression for Non-Euclidean Responses and Predictors Jeong Min Jeon, Byeong U Park, and Ingrid Van Keilegom
Set structured global empirical risk minimizers are rate optimal in general dimensions Qiyang Han
Empirical tail copulas for functional data John H.J. Einmahl and Johan Segers
Inference for a two-stage enrichment design Zhantao Lin, Nancy Flournoy, and William Rosenberger
Existence and Uniqueness of the Kronecker Covariance MLE Mathias Drton, Satoshi Kuriki, and Peter Hoff
Willem van Zwet’s contributions to the profession Nicholas Fisher and Adrian Smith
Prediction bounds for higher order total variation regularized least squares Francesco Ortelli and Sara van de Geer
Reconciling the Gaussian and Whittle Likelihood with an application to estimation in the frequency domain Suhasini Subba Rao and Junho Yang
Integrative Methods for Post-Selection Inference Under Convex Constraints Snigdha Panigrahi, Jonathan Taylor, and Asaf Weinstein
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy Tony Cai, Yichen Wang, and Linjun Zhang
Adaptive Estimation of Multivariate Regression with Hidden Variables Xin Bing
Willem van Zwet’s Research Peter Bickel, Marta Fiocco, Mathisca de Gunst, and Friedrich Götze
An Optimal Statistical and Computational Framework for Generalized Tensor Estimation Rungang Han, Rebecca Willett, and Anru Zhang
Distributed Statistical Inference for Massive Data Song X Chen and Liuhua Peng
Construction of Mixed Orthogonal Arrays with High Strength Shanqi Pang, Jing Wang, Dennis K.J. Lin, and Min-qian Liu
Foundations of Structural Causal Models with Cycles and Latent Variables Stephan Bongers, Patrick Forré, Jonas Peters, and Joris Mooij
Measuring dependence in the Wasserstein distance for Bayesian nonparametric models Marta Catalano, Antonio Lijoi, and Igor Pruenster
Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data Yuxin Chen, Jianqing Fan, Cong Ma, and Yuling Yan
Spatial dependence and space-time trend in extreme events John Einmahl, Ana Ferreira, Laurens de Haan, Claudia Neves, and Chen Zhou
Efficiency of delayed-acceptance random walk Metropolis algorithms Chris Sherlock, Alexandre H Thiery, and Andrew Golightly
Willem van Zwet, teacher and thesis advisor Sara van de Geer and Chris A.J. Klaassen
Semiparametric Optimal Estimation with Nonignorable Nonresponse Data Kosuke Morikawa and Jae Kwang Kim
Two-Level Parallel Flats Designs Chunyan Wang and Robert W Mee
Estimating the number of components in finite mixture models via the group-sort-fuse procedure Tudor Manole and Abbas Khalili
A simple measure of conditional dependence Mona Azadkia and Sourav Chatterjee
Heteroskedastic PCA: Algorithm, Optimality, and Applications Anru Zhang, T. Tony Cai, and Yihong Wu
Online Inference with Multi-Modal Likelihood Functions Mathieu Gerber and Kari Heine
On Fixed-Domain Asymptotics, Parameter Estimation and Isotropic Gaussian Random Fields with Matern Covariance Functions Wei-Liem Loh, Saifei Sun, and Jun Wen
Adaptive Learning Rates for Support Vector Machines Working on Data with Low Intrinsic Dimension Thomas Hamm and Ingo Steinwart
Community Detection on Mixture Multi-Layer Networks Via Regularized Tensor Decomposition Bing-Yi Jing, Ting Li, Zhongyuan Lyu, and Dong Xia
Augmented Minimax Linear Estimation David Abraham Hirshberg and Stefan Wager
Wilks’ Theorem for Semiparametric Regressions with Weakly Dependent Data Marie du Roy de Chaumaray, Matthieu Marbac, and Valentin Patilea
Statistical guarantees for Bayesian uncertainty quantification in non-linear inverse problems with Gaussian process priors Francois Monard, Richard Nickl, and Gabriel Paternain
Marginal Singularity, and the Benefits of Labels in Covariate-Shift Samory Kpotufe and Guillaume Martinet
Optimal Linear Discriminators For The Discrete Choice Model In Growing Dimensions Debarghya Mukherjee, Moulinath Banerjee, and Ya’acov Ritov
On Minimax Optimality of Sparse Bayes Predictive Density Estimates Gourab Mukherjee and Iain M Johnstone
Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models Stephane Girard, Gilles Stupfler, and Antoine Usseglio-Carleve
Asymptotic Properties of Penalized Spline Estimators in Concave Extended Linear Models: Rates of Convergence Jianhua Huang and Ya Su
Optimal adaptivity of Signed-Polygon statistics for network testing Jiashun Jin, Tracy Ke, and Shengming Luo
Analysis of Generalized Bregman surrogate Algorithms for Nonsmooth Nonconvex Statistical Learning Yiyuan She, Zhifeng Wang, and Jiuwu Jin
Dimension reduction for functional data based on weak conditional moments Bing Li and Jun Song
An asymptotic test for constancy of the variance under short-range dependence Sara Kristin Schmidt, Max Wornowizki, Roland Fried, and Herold Dehling
Uncertainty quantification for Bayesian CART Ismael Castillo and Veronika Rockova
Pattern Graphs: a Graphical Approach to Nonmonotone Missing Data Yen-Chi Chen
Total Variation Regularized Fréchet Regression for Metric-Space Valued Data Zhenhua Lin and Hans-Georg Müller
Posterior consistency for N in the binomial (N,P) problem with both parameters unknown – with applications to quantitative nanoscopy Laura Fee Schneider, Johannes Anselm Schmidt-Hieber, Thmoas Staudt, Andrea Krajina, Timo Aspelmeier, and Axel Munk
Multiscale Bayesian Survival Analysis Ismaël Castillo and Stéphanie van der Pas
Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators Axel Bücher, Holger Dette, and Florian Heinrichs
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
Adaptive transfer learning Henry W. J. Reeve, Timothy I. Cannings, and Richard J. Samworth
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
Preface: Section of memorial articles for Willem van Zwet Richard J. Samworth and Ming Yuan
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