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Papers to Appear in Subsequent Issues

Fully Adaptive Density-Based Clustering

Ingo Steinwart

Minimax Estimation in Sparse Canonical Correlation Analysis

Harrison Zhou, Chao Gao, Zongming Ma, and Zhao Ren

Computing exact D-optimal designs by mixed integer second order cone programming

Guillaume Sagnol and Radoslav Harman

Globally adaptive quantile regression with ultra-high dimensional data

Qi Zheng, Limin Peng, and Xuming He

On adaptive posterior concentration rates

Marc Hoffmann, Judith Rousseau, and Johannes Schmidt-Hieber

Functional Additive Regression

Yingying Fan, Gareth James, and Peter Radchenko

Statistical and computational trade-offs in estimation of sparse principal components

Tengyao Wang, Quentin Berthet, and Richard John Samworth

Exact Post-Selection Inference, with Application to the Lasso

Jason D Lee, Dennis L Sun, Yuekai Sun, and Jonathan E Taylor

Nonparametric Modal Regression

Yen-Chi Chen, Christopher R. Genovese, Ryan J. Tibshirani, and Larry Wasserman

Local Independence Feature Screening for Nonparametric and Semiparametric Models by Marginal Empirical Likelihood

Jinyuan Chang, Cheng Yong Tang, and Yichao Wu

Cramér Type Moderate Deviations for Studentized Two-Sample U-statistics with Applications

Jinyuan Chang, Qi-Man Shao, and Wen-Xin Zhou

Estimating multivariate latent-structure models

Koen Jochmans, Stephane Bonhomme, and Jean-Marc Robin

Optimal Shrinkage Estimation of Mean Parameters in Family of Distributions with Quadratic Variance

Xianchao Xie, Samuel Kou, Lawrence Brown

Large sample behaviour of high dimensional autocovariance matrices

Monika Bhattacharjee and Arup Bose

Estimation in Nonlinear Regression with Harris Recurrent Markov Chains

Degui Li, Dag Tjostheim, and Jiti Gao

Global solutions to folded concave penalized nonconvex learning

Hongcheng Liu, Tao Yao, and Runze Li

Batched Bandit Problems

Vianney Perchet, Philippe Rigollet, Sylvain Chassang, and Erik Snowberg

Optimal Large-Scale Quantum State Tomography with Pauli Measurements

Yazhen Wang, Tony Cai, Donggyu Kim, Ming Yuan, and Harrison Zhou

Statistical Inference for the Mean Outcome Under a Possibly Non-Unique Optimal Treatment Strategy

Alexander R Luedtke and Mark J van der Laan

Efficient estimation in semivarying coefficient models for longitudinal/clustered data

Ming-Yen Cheng, Toshio Honda, and Jialiang Li

Inference in Adaptive Regression via the Kac-Rice formula

Jonathan Edward Taylor, Joshua Loftus, and Ryan Tibshirani

Amplitude and Phase Variation of Generalised Functional Data

Victor Michael Panaretos and Yoav Zemel

Best Subset Selection via a Modern Optimization Lens

Dimitris Bertsimas, Angela King, and Rahul Mazumder

Estimation in exponential families on permutations

Sumit Mukherjee

Bayesian manifold regression

Yun Yang and David B. Dunson

Non-Parametric Stochastic Approximation with large step sizes

Aymeric Dieuleveut and Francis Bach

Partial Correlation Screening for estimating large precision matrices, with applications to classification

Jiashun Jin, Shiqiong Huang Huang, and Zhigang Yao

Nonparametric Eigenvalue-Regularized Precision or Covariance Matrix Estimator

Clifford Lam

Global Rates of Convergence of the MLEs of Log-Concave and S-Concave Densities

Charles R Doss and Jon A Wellner

Classification with the nearest neighbor rule in general finite dimensional spaces

Sébastien Gadat, Thierry Klein, and Clément Marteau

A new prior for discrete DAG models with a restricted set of directions

Helene Menexia Massam and Jacek Wesolowski

Slope is Adaptive to Unknown Sparsity and Asymptotically Minimax

Weijie Su and Emmanuel Candes

Supremum Norm Posterior Contraction and Credible Sets for Nonparametric Multivariate Regression

William Weimin Yoo and Subhashis Ghosal

Optimal designs for comparing curves

Holger Dette and Kirsten Schorning

Randomization-based models for multitiered experiments: I. A chain of randomizations

Rosemary Anne Bailey and Christopher J. Brien

Vector Quantile Regression: An Optimal Transport Approach

Guillaume Carlier, Victor Chernozhukov, and Alfred Galichon

Local intrinsic stationarity and its inference

Tailen Hsing, Thomas Brown, and Brian Thelen

Structure Identification in Panel Data Analysis

Yuan Ke, Jialiang Li, and Wenyang Zhang

Inference for Single-index Quantile Regression Models with Profile Optimization

Shujie Ma and Xuming He

Theoretical Analysis of Nonparametric Filament Estimation

Wanli Qiao and Wolfgang Polonik

Semiparametric efficient estimation for shared-frailty models with doubly-censored clustered data

Yu-Ru Su and Jane-Ling Wang

An unexpected encounter with Cauchy and Levy

Natesh S Pillai and Xiao-Li Meng

Approximation and estimation of s-concave densities via Renyi divergences

Qiyang (Roy) Han and Jon A. Wellner

Nonparametric estimation of dynamics of monotone trajectories

Debashis Paul, Jie Peng, and Prabir Burman

A Partially Linear Framework for Massive Heterogeneous Data

Tianqi Zhao, Guang Cheng, and Han Liu

Causal Inference with a Graphical Hierarchy of Interventions

Ilya Shpitser and Eric Tchetgen Tchetgen

Global Testing Against Sparse Alternatives in Time-Frequency Analysis

Tony Cai, Yonina C. Eldar, and Xiaodong Li

Consistent model selection criteria for quadratically supported risks

Yongdai Kim and Jong-June Jeon

Tensor decompositions and sparse log-linear models

James Edward Johndrow, Anirban Bhattacharya, and David Dunson

Correction note to "Limit Theorems for Empirical Processes of Cluster Functionals"

Holger Drees and Holger Rootzén

Innovated Scalable Efficient Estimation in Ultra-Large Gaussian Graphical Models

Yingying Fan and Jinchi Lv

On the computational complexity of high-dimensional Bayesian variable selection

Yun Yang, Martin J. Wainwright, and Michael I. Jordan

Family wise separation rates for multiple testing

Magalie Fromont, Matthieu Lerasle, and Patricia Reynaud-Bouret

Sieve-based inference for infinite-variance linear processes

Giuseppe Cavaliere, Iliyan Georgiev, and A.M.Robert Taylor

Information Geometry Approach to Parameter Estimation in Markov Chains

Masahito Hayashi and Shun Watanabe

On High-dimensional Misspecified Mixed Model Analysis in Genome-wide Association Study

Jiming Jiang, Cong Li, Debashis Paul, Can Yang, and Hongyu Zhao

Minimax Optimal Rates of Estimation in High Dimensional Additive Models: Universal Phase Transition

Ming Yuan and Ding-Xuan Zhou

Influential Features PCA for high dimensional clustering

Jiashun Jin and Wanjie Wang

On Marginal Sliced Inverse Regression For Ultrahigh Dimensional Model Free Feature Selection

Zhou Yu, Yuexiao Dong, and Jun Shao

Faithful variable screening for high-dimensional convex regression

Min Xu, Minhua Chen, and John Lafferty

Geometric Inference for General High-Dimensional Linear Inverse Problems

T. Tony Cai, Tengyuan Liang, and Alexander Rakhlin

The Tracy-Widom law for the Largest Eigenvalue of F Type Matrices

Xiao Han, Guangming Pan, and Bo Zhang

Minimax Rates of Community Detection in Stochastic Block Models

Anderson Y. Zhang and Harrison H. Zhou

Self-normalized Cramer Type Moderate Deviations under Dependence

Xiaohong Chen, Qi-Man Shao, Wei Wu, and Lihu Xu

Estimation of Semi-Varying Coefficient Time Series Models With ARMA Errors

Lei Huang and Yingcun Xia

High-Dimensional Generalizations of Asymmetric Least Squares Regression and Their Applications

Yuwen Gu and Hui Zou

Minimax estimation of linear and quadratic functionals on sparsity classes

Olivier Collier, Laetitia Comminges, and Alexandre Tsybakov

Mimicking counterfactual outcomes to estimate causal effects

Judith Jacqueline Lok

A lava attack on the recovery of sums of dense and sparse signals

Victor Chernozhukov, Christian Hansen, and Yuan Liao

Statistical Guarantees for the EM Algorithm: From Population to Sample-Based Analysis

Sivaraman Balakrishnan, Martin J Wainwright, and Bin Yu

Discriminating quantum states: the multiple Chernoff distance

Ke Li

Normal approximation and concentration of spectral projectors of sample covariance

Vladimir Koltchinskii and Karim Lounici

Asymptotic Theory for the First Projective Direction

Michael G. Akritas

Higher order elicitability and Osband's principle

Tobias Fissler and Johanna F. Ziegel

Sub-Gaussian mean estimators

Luc Devroye, Matthieu Lerasle, Gabor Lugosi, and Roberto Imbuzeiro Oliveira

Optimal Estimation for the Functional Cox Model

Simeng Qu, Jane-Ling Wang, and Xiao Wang

Nonparametric covariate-adjusted regression

Aurore Delaigle, Peter Hall, and Wen-Xin Zhou

Optimal Rates of Convergence for Noisy Sparse Phase Retrieval via Thresholded Wirtinger Flow

T.Tony Cai, Xiaodong Li, and Zongming Ma

Convergence rates of parameter estimation for some weakly identifiable finite mixtures

Nhat Ho and XuanLong Nguyen

Solution of linear ill-posed problems using overcomplete dictionaries

Marianna Pensky

From Sparse to Dense Functional Data and Beyond

Xiaoke Zhang and Jane-Ling Wang

Impact of regularization on spectral clustering

Antony Joseph and Bin Yu

A General Theory of Hypothesis Tests and Confidence Regions for Sparse High Dimensional Models

Yang Ning and Han Liu

A Bayesian Approach for Envelope Models

Kshitij Khare, Subhadip Pal, and Zhihua Su

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