Papers to Appear in Subsequent Issues

Computation of Maximum Likelihood Estimates in Cyclic Structural Equation Models Mathias Drton, Christopher Fox, and Y. Samuel Wang
Exact recovery in the Ising blockmodel Quentin Berthet, Philippe Rigollet, and Piyush Srivastava
Fréchet regression for random objects with Euclidean Predictors Alexander Petersen and Hans-Georg Müller
Divide and Conquer in Non-Standard Problems and the Super-Efficiency Phenomenon Moulinath Banerjee, Cecile Durot, and Bodhisattva Sen
Rank Verification for Exponential Families Kenneth Hung and William Fithian
Sub-Gaussian estimators of the mean of a random vector Gábor Lugosi and Shahar Mendelson
Combinatorial Inference for Graphical Models Matey Neykov, Junwei Lu, and Han Liu
Estimation and Prediction using generalized Wendland Covariance Functions under fixed domain asymptotics Moreno Bevilacqua, Tarik Faouzi, Reinhard Furrer, and Emilio Porcu
Chebyshev polynomials, moment matching, and optimal estimation of the unseen Yihong Wu and Pengkun Yang
Maximuim likelihood estimation in Gaussian models under total positivity Steffen Lilholt Lauritzen, Caroline Uhler, and Piotr Zwiernik
Partial Least Squares Prediction in High-Dimensional Regression R. Dennis Cook and Liliana Forzani
Signal Aliasing in Gaussian Random Fields for Experiments with Qualitative Factors Ming-Chung Chang, Shao-Wei Cheng, and Ching-Shui Cheng
Cross: Efficient Low-rank Tensor Completion Anru Zhang
Testing in High-Dimensional Spiked Models Iain M Johnstone and Alexei Onatski
Covariate balancing propensity score by tailored loss functions Qingyuan Zhao
The geometry of hypothesis testing over convex cones: Generalized likelihood ratio tests and minimax radii Yuting Wei
Nonparametric Implied Levy Densities Likuan Qin and Viktor Todorov
On model selection from a finite family of possibly misspecified time series models Hsiang-Ling Hsu, Ching-Kang Ing, and Howell Tong
Estimating the Algorithmic Variance of Randomized Ensembles via the Bootstrap Miles Lopes
Efficient Nonparametric Bayesian Inference for X-ray transforms Francois Monard, Richard Nickl, and Gabriel P Paternain
Generalized Random Forests Susan Athey, Julie Tibshirani, and Stefan Wager
Approximating faces of marginal polytopes in discrete hierarchical models Nanwei Wang, Johannes Rauh, and Helene Massam
CHIME: Clustering of High-Dimensional Gaussian Mixtures with EM Algorithm and Its Optimality Tony Cai, Jing Ma, and Linjun Zhang
Bayesian fractional posteriors Anirban Bhattacharya, Debdeep Pati, and Yun Yang
Distributed Estimation of Principal Eigenspaces Jianqing Fan, Dong Wang, Kaizheng Wang, and Ziwei Zhu
Exponential ergodicity of the Bouncy Particle Sampler George Deligiannidis, Alexandre Bouchard-Cote, and Arnaud Doucet
The Zig-Zag process and Super-Efficient Sampling for Bayesian Analysis of Big Data Joris Bierkens, Paul Fearnhead, and Gareth O. Roberts
Estimation of Large Covariance and Precision Matrices from Temporally Dependent Observations Hai Shu and Bin Nan
Bootstrap tuning in ordered model selection Vladimir Spokoiny and Niklas Willrich
Sequential change-point detection based on nearest neighbors Hao Chen
Prediction when fitting simple models to high-dimensional data Lukas Steinberger and Hannes Leeb
Two-Sample and ANOVA Tests for High Dimensional Means Song X Chen, Jun Li, and Pingshou Zhong
Valid confidence intervals for post-model-selection predictors François Bachoc, Hannes Leeb, and Benedikt Poetscher
A robust and efficient approach to causal inference based on sparse sufficient dimension reduction Shujie Ma, Liping Zhu, Zhiwei Zhang, Chih-Ling Tsai, and Raymond Carroll
A Classification Criterion for Definitive Screening Designs Eric Schoen, Pieter Eendebak, and Peter Goos
The Maximum Likelihood Threshold of a Path Diagram Mathias Drton, Christopher Fox, Andreas Käufl, and Guillaume Pouliot
Convex Regularization for High-dimensional Multi-response Tensor Regression Garvesh Raskutti, Ming Yuan, and Han Chen
Maximum likelihood estimation in transformed linear regression with non-normal errors Xingwei Tong, Fuqing Gao, Kani Chen, Dingjiao Cai, and Jianguo Sun
Large Sample Theory for Merged Data from Multiple Sources Takumi Saegusa
Khinchine’s theorem and Edgeworth approximations for weighted sums Sergey G. Bobkov
Hypothesis Testing for Densities and High-Dimensional Multinomials: Sharp Local Minimax Rates Sivaraman Balakrishnan and Larry Wasserman
Distributed Inference for Quantile Regression Processes Stanislav Volgushev, Shih-Kang Chao, and Guang Cheng
Gaussian approximation of maxima of Wiener functionals and its application to high-frequency data Yuta Koike
Causal Dantzig: fast inference in linear structural equation models with hidden variables under additive interventions Dominik Rothenhäusler, Peter Bühlmann, and Nicolai Meinshausen
Non-penalized variable selection in high-dimensional linear model settings via generalized fiducial inference Jonathan Paul Williams and Jan Hannig
The BLUE in regression models with correlated errors Holger Dette, Andrey Pepelyshev, and Anatoly Zhigljavsky
Adaptive-to-model checking for regressions with diverging number of predictors Falong Tan and Lixing Zhu
Super-resolution estimation of cyclic arrival rates Ningyuan Chen, Donald K.K. Lee, and Sahand N. Negahban
Sequential Multiple Testing with Generalized Error Control: An Asymptotic Optimality Theory Yanglei Song and Georgios Fellouris
Nonparametric Screening under Conditional Strictly Convex Loss for Ultrahigh Dimensional Sparse Data Xu Han
Local stationarity and time-inhomogeneous Markov chains Lionel Truquet
High-dimensional change-point detection with sparse alternatives Farida Enikeeva and Zaid Harchaoui
Perturbation Bootstrap in Adaptive Lasso Debraj Das, Karl Gregory, and Soumendra Nath Lahiri
Estimation bounds and sharp oracle inequalities of regularized procedures with Lipschitz loss functions Guillaume Lecue, Pierre Alquier, and Vincent Cottet
Cross validation for locally stationary processes Stefan Richter and Rainer Dahlhaus
Generalized Cluster Trees and Singular Measures Yen-Chi Chen
Spectral Method and Regularized MLE are Both Optimal for Top-K Ranking Yuxin Chen, Jianqing Fan, Cong Ma, and Kaizheng Wang
Negative association, ordering and convergence of resampling methods Mathieu Gerber, Nicolas Chopin, and Nick Whiteley
On deep learning as a remedy for the curse of dimensionality in nonparametric regression Benedikt Bauer and Michael Kohler
Convergence rates of least squares regression estimators with heavy tailed errors Qiyang Han and Jon A. Wellner
Convergence complexity analysis of Albert and Chib’s algorithm for Bayesian probit regression Qian Qin and James P. Hobert
On Testing Conditional Qualitative Treatment Effects Chengchun Shi, Wenbin Lu, and Rui Song
Dynamic network models and graphon estimation Marianna Pensky
The two-to-infinity norm and singular subspace geometry with applications to high-dimensional statistics Joshua Cape, Minh Tang, and Carey E. Priebe
Isotonic regression in general dimensions Qiyang Han, Tengyao Wang, Sabyasachi Chatterjee, and Richard John Samworth
Property Testing in High Dimensional Ising Models Matey Neykov and Han Liu
A knockoff filter for high-dimensional selective inference Rina Foygel Barber and Emmanuel J Candes
Semi-supervised Inference: General Theory and Estimation of Means Anru Zhang, Lawrence D. Brown, and T. Tony Cai
Penalized Estimation in Additive Regression with High-Dimensional Data Zhiqiang Tan and Cun-Hui Zhang
Semiparametrically Optimal Hybrid Rank Tests for Unit Roots Bo Zhou, Ramon van den Akker, and Bas Werker
Sorted Concave Penalized Regression Long Feng and Cun-Hui Zhang
The middle-scale asymptotics of Wishart matrices Didier Chételat and Martin T. Wells
Linear hypothesis testing for high dimensional generalized linear models Chengchun Shi, Rui Song, Zhao Chen, and Runze Li
An Operator Theoretic Approach to Nonparametric Mixture Models Robert Anton Vandermeulen and Clayton Scott
Phase transition in the spiked random tensor with Rademacher prior Wei-Kuo Chen
Distance multivariance: New dependence measures for random vectors Björn Böttcher, Martin Keller-Ressel, and Rene L. Schilling
A Unified Treatment of Multiple Testing with Prior Knowledge using the p-filter Aaditya K. Ramdas, Rina F. Barber, Martin J. Wainwright, and Michael I. Jordan
Exact Lower Bounds for the Agnostic Probably-Approximately-Correct (PAC) Machine Learning Model Iosif Pinelis and Aryeh Kontorovich
Eigenvalue distributions of variance components estimators in high-dimensional random effects models Zhou Fan and Iain Johnstone
Global Test Statistics for High Dimensional  Correlation Matrices S. R. Zheng, Guanghui Cheng, Jianhua Guo, and Hongtu Zhu
Projected Spline Estimation of the Nonparametric Function in High-dimensional Partially Linear Models for Massive Data Heng Lian, Kaifeng Zhao, and Shaogao Lv
Inference for the mode of a log-concave density Charles R. Doss and Jon A. Wellner
Testing for Independence of Large Dimensional Vectors Taras Bodnar, Holger Dette, and Nestor Parolya
Active Ranking from Pairwise Comparisons and When Parametric Assumptions Don’t Help Reinhard Heckel, Nihar B. Shah, Kannan Ramchandran, and Martin J. Wainwright
Randomized incomplete U-statistics in high dimensions Xiaohui Chen and Kengo Kato
Adaptive estimation of the rank of the coefficient matrix in high dimensional multivariate response regression models Xin Bing and Marten Wegkamp
Statistical inference for autoregressive models under heteroscedasticity of unknown form Ke Zhu
On Partial-Sum Processes of ARMAX Residuals Steffen Grønneberg and Benjamin Holcblat
Quantile Regression Under Memory Constraint Xi Chen, Weidong Liu, and Yichen Zhang
Sampling and Estimation for (Sparse) Exchangeable Graphs Victor Veitch and Daniel Murphy Roy
Hypothesis Testing on Linear Structures of High Dimensional Covariance Matrix Shurong Zheng, Zhao Chen, Hengjian Cui, and Runze Li
On optimal designs for non-regular models Yi Lin, Ryan Martin, and Min Yang
A Smeary Central Limit Theorem for Manifolds with Application to High Dimensional Spheres Benjamin Eltzner and Stephan F. Huckemann
On testing for high-dimensional white noise Zeng Li, Jianfeng Yao, Clifford Lam,  and Qiwei Yao
Minimax Posterior Convergence Rates and Model Selection Consistency in High-dimensional DAG Models based on Sparse Cholesky Factors Kyoungjae Lee, Jaeyong Lee, and Lizhen Lin
Bootstrapping and Sample Splitting for High-Dimensional, Assumption-Free Inference Alessandro Rinaldo, Max G’Sell, Jing Lei, and Larry Wasserman
Joint convergence of sample autocovariance matrices when p/n → 0 with application Monika Bhattacharjee and Arup Bose
Tracy-Widom limit for Kendall’s tau Zhigang Bao
Intrinsic Riemannian Functional Data Analysis Zhenhua Lin and Fang Yao
Two-Step Semiparametric Empirical Likelihood Inference Francesco Bravo, Juan Carlos Escanciano, and Ingrid Van Keilegom
The Phase Transition for the Existence of the Maximum Likelihood Estimate in High-Dimensional Logistic Regression Emmanuel Jean Candes and Pragya Sur
Rerandomization in 2K Factorial Experiments Peng Ding, Xinran Li, and Donald Bruce Rubin
Sparse Sir: Optimal Rates and Adaptive Estimation Kai Tan, Lei Shi, and Zhou Yu
On Estimation of Isotonic Piecewise Constant Signals Chao Gao, Fang Han, and Cun-Hui Zhang
Robust Sparse Covariance Estimation by Thresholding Tyler’s M-Estimator John Goes, Gilad Lerman, and Boaz Nadler
Model-assisted variable clustering: minimax-optimal recovery and algorithms Florentina Bunea, Christophe Giraud, Martin Royer, Nicolas Verzelen, and Xi Luo
The New G-Formula for the Sequential Causal Effect and the Blip Effect of Treatment in Sequential Causal Inference Xiaoqin Wang and Li Yin
Envelope-Based Sparse Partial Least Squares Guangyu Zhu and Zhihua Su
Optimal Rates for Community Estimation in the Weighted Stochastic Block Model Min Xu, Varun Jog, and Po-Ling Loh
Limiting Laws for Divergent Spiked Eigenvalues and Largest Non-spiked Eigenvalue of Sample Covariance Matrices Tony Cai, Xiao Han, and Guangming Pan