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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

Strong orthogonal arrays of strength two plus

Yuanzhen He, Ching-Shui Cheng, and Boxin Tang
Statistical inference for spatial statistics defined in the Fourier domain Suhasini Subba Rao

On the inference about the spectral distribution of high-dimensional covariance matrix based on high-frequency noisy observations

Ningning Xia and Xinghua Zheng

Online Rules for Control of False Discovery Rate and False Discovery Exceedance

Adel Javanmard and Andrea Montanari

Frequency Domain Minimum Distance Inference for Possibly Noninvertible and Noncausal ARMA models

Carlos Velasco and Ignacio N. Lobato

On consistency and sparsity for sliced inverse regression in high dimensions

Qian Lin, Zhigen Zhao, and Jun S. Liu

Regularization and the small-ball method I: sparse recovery

Guillaume Lecue and Shahar Mendelson

Gaussian and bootstrap approximations for high-dimensional U-statistics and their applications

Xiaohui Chen

Selective inference with a randomized response

Xiaoying Tian and Jonathan Taylor

Multiscale Blind Source Separation

Merle Behr, Chris Holmes, and Axel Munk

Sharp oracle inequalities for Least Squares estimators in shape restricted regression

Pierre C. Bellec

Oracle Inequalities for Sparse Additive Quantile Regression in Reproducing Kernel Hilbert Space

Shaogao Lv, Huazhen Lin, Heng Lian, and Jian Huang

I-LAMM: Simultaneous Control of Algorithmic Complexity and Statistical Error

Jianqing Fan, Han Liu, Qiang Sun, and Tong Zhang

On Bayesian index policies for sequential resource allocation

Emilie Kaufmann

High-Dimensional A-Learning for Optimal Dynamic Treatment Regimes

Chengchun Shi, Ailin Fan, Rui Song, and Wenbin Lu

Testing independence with high-dimensional correlated samples

Xi Chen and Weidong Liu

Variable selection with Hamming loss

Cristina Butucea, Natalia A. Stepanova, and Alexandre B. Tsybakov

Test for High Dimensional Regression Coefficients Using Refitted Cross-Validation Variance Estimation

Hengjian Cui, Wenwen Guo, and Wei Zhong

Detecting Rare and Faint Signals via Thresholding Maximum Likelihood Estimators

Yumou Qiu, Song X Chen, and Dan Nettleton

Are Discoveries Spurious? Distributions of Maximum Spurious Correlations and Their Applications

Jianqing Fan, Qi-Man Shao, and Wenxin Zhou

Adaptive estimation of planar convex sets

Tony Cai, Adityanand Guntuboyina, and Yuting Wei

High-dimensional consistency of AIC and BIC for estimating the number of significant components in principal component analysis

Zhidong Bai, Yasunori Fujikoshi, and Kwok Pui Choi

On the systematic and idiosyncratic volatility with large panel high-frequency data

Xinbing Kong

Ball Divergence: Multivariate Imbalance Test

Wenliang Pan, Yuan Tian, Xueqin Wang, and Heping Zhang

Asymptotic distribution-free tests for semiparametric regressions with dependent data

Juan Carlos Escanciano, Juan Carlos Pardo Fernandez, and Ingrid Van Keilegom

A Smooth Block Bootstrap for Quantile Regression with Time Series

Karl B Gregory, Soumendra N Lahiri, and Dan J Nordman

Gradient-Based Structural Change Detection For Non-stationary Time Series M-estimation

Weichi Wu and Zhou Zhou

Moderate Deviations and Nonparametric Inference for Monotone Functions

Fuqing Gao, Jie Xiong, and Xingqiu Zhao

Uniform Asymptotic Inference and the Bootstrap After Model Selection

Ryan Joseph Tibshirani, Alessandro Rinaldo, Robert Tibshirani, and Larry Wasserman

Detection Thresholds for the β-Model on Sparse Graphs

Rajarshi Mukherjee, Sumit Mukherjee, and Subhabrata Sen

Minimax and adaptive estimation of the Wigner function in quantum homodyne tomography with noisy data

Karim Lounici, Katia Meziani, and Gabriel Peyre

Distributed Testing and Estimation under Sparse High Dimensional Models

Heather Battey, Jianqing Fan, Han Liu, Junwei Lu, and Ziwei Zhu

Large Covariance Estimation Through Ellipitical Factor Models

Jianqing Fan, Han Liu, and Weichen Wang

Current status linear regression

Piet Groeneboom and Kim Hendrickx

Functional Data Analysis by Matrix Completion

Marie-Hélène Descary and Victor Michael Panaretos

Jump filtering and efficient drift estimation for Lévy-driven SDE's

Arnaud Gloter, Hilmar Mai, and Dasha Loukianova

Consistency and convergence rate of phylogenetic inference via regularization

Vu Dinh, Lam Si Tung Ho, Marc Suchard, and Frederick Matsen

Pareto Quantiles of Unlabeled Tree Objects

Ela Sienkiewicz and Haonan Wang

Efficient and Adaptive Linear Regression in Semi-Supervised Settings

Abhishek Chakrabortty and Tianxi Cai

Convexified Modularity Maximization for Degree-corrected Stochastic Block Models

Yudong Chen, Xiaodong Li, and Jiaming Xu

Near-Optimality of Linear Recovery in Gaussian Observation Scheme under ||·|| 22-Loss

Anatoli B. Juditsky and Arkadi S. Nemirovski

An MCMC Approach to Empirical Bayes Inference and Bayesian Sensitivity Analysis via Empirical Processes

Hani John Doss and Yeonhee Park

Curvature and inference for maximum likelihood estimates

Bradley Efron

Empirical Bayes Estimates for a 2-Way Cross-Classified Additive Model

Lawrence D Brown, Gourab Mukherjee, and Asaf Weinstein
Estimating Variance of Random Effects to Solve to Multiple Problems Simultaneously Masayo Yoshimori Hirose and Partha Lahiri

Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model

David L Donoho, Matan Gavish, and Iain M Johnstone

Computation of Maximum Likelihood Estimates in Cyclic Structural Equation Models

Mathias Drton, Christopher Fox, and Y. Samuel Wang

A Bayesian Approach to the Selection of Two-Level Multi-Stratum Factorial Designs

Ming-Chung Chang and Ching-Shui Cheng

Accuracy Assessment for High-dimensional Linear Regression

Tony Cai and Zijian Guo

Randomization-based causal inference from split-plot designs

Anqi Zhao, Peng Ding, Rahul Mukerjee, and Tirthankar Dasgupta

A New Perspective on Robust M-Estimation: Finite Sample Theory and Applications to Dependence-Adjusted Multiple Testing

Wen-Xin Zhou, Koushiki Bose, Jianqing Fan, and Han Liu

Robust Covariance and Scatter Matrix Estimation under Huber's Contamination Model

Mengjie Chen, Chao Gao, and Zhao Ren

Empirical best prediction under a nested error model with log transformation

Isabel Molina and Nirian Martin

Backward Nested Descriptors Asymptotics with Inference on Stem Cell Differentiation

Stephan Huckemann and Benjamin Eltzner

Change-point detection in multinomial data with a large number of categories

Guanghui Wang, Changliang Zou, and Guosheng Yin

Local Asymptotic Normality Property for Fractional Gaussian Noise Under High-Frequency Observations

Masaaki Fukasawa and Alexandre Brouste

Global Testing Against Sparse Alternatives under Ising Models

Rajarshi Mukherjee, Sumit Mukherjee, and Ming Yuan

Principal Component Analysis for Second-order Stationary Vector Time Series

Jinyuan Chang, Bin Guo, and Qiwei Yao

Estimation of a monotone density in s-sample biased sampling models

Kwun Chuen Gary Chan, Hok Kan Ling, Tony Sit, and Sheung Chi Phillip Yam

Community Detection in Degree-Corrected Block Models

Chao Gao, Zongming Ma, Anderson Zhang, and Harrison Zhou

CLT for Largest Eigenvalues and Unit Root Testing for High-Dimensional Nonstationary Time Series

Guangming Pan, Bo Zhang, and Jiti Gao

Smooth Backfitting for Errors-in-Variables Additive Models

Kyunghee Han and Byeong U Park

Unifying Markov Properties for Graphical Models

Steffen Lilholt Lauritzen and Kayvan Sadeghi

Adaptation in log-concave density estimation

Arlene Kyoung Hee Kim, Adityanand Guntuboyina, and Richard John Samworth

Exact recovery in the Ising blockmodel

Quentin Berthet, Philippe Rigollet, and Piyush Srivastava

Weak convergence of a pseudo maximum likelihood estimator for the extremal index

Betina Berghaus and Axel Bücher

Semi-parametric efficiency bounds for high-dimensional models

Jana Jankova and Sara van de Geer

Limit theorems for eigenvectors of the normalized Laplacian for random graphs

Minh Tang and Carey Priebe

Fréchet regression for random objects with Euclidean Predictors

Alexander Petersen and Hans-Georg Müller

On the Optimality and Sub-optimality of PCA in Spiked Random Matrix Models

Amelia Perry, Alexander S. Wein, Afonso S. Bandeira, and Ankur Moitra

On the Exponentially Weighted Aggregate with the Laplace Prior

Arnak Dalalyan, Edwin Grappin, and Quentin Paris

Goodness-of-fit Testing of Error Distribution in Linear Measurement Error Models

Hira L. Koul, Weixing Song, and Xiaoqing Zhu

Finding a Large Submatrix of a Gaussian Random Matrix

David Gamarnik and Quan Li

Support Points

Simon Mak and V. Roshan Joseph

Debiasing the Lasso: Optimal Sample Size for Gaussian Designs

Adel Javanmard and Andrea Montanari

Margins of Discrete Bayesian Networks

Robin Evans

Multi-threshold Accelerated Failure Time Model

Jialiang Li and Baisuo Jin

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

Measuring and testing for interval quantile independence

Liping Zhu, Yaowu Zhang, and Kai Xu

Barycentric Subspace Analysis on Manifolds

Xavier Pennec

The Landscape of Empirical Risk for Non-convex Losses

Song Mei, Yu Bai, and Andrea Montanari

Designs with Blocks of Size Two and Applications to Microarray Experiments

Janet Godolphin

Sub-Gaussian estimators of the mean of a random vector

Gábor Lugosi and Shahar Mendelson

Local robust estimation of the Pickands dependence function

Mikael Escobar-Bach, Yuri Goegebeur, and Armelle Guillou

Optimal rates for finite mixture estimation

Jonas Kahn and Philippe Heinrich

Sub-Gaussian estimators of the mean of a random matrix with heavy-tailed entries

Stanislav Minsker

Causal Inference in Partially Linear Structural Equation Models: Identifiability and Estimation

Dominik Rothenhäusler, Jan Ernest, and Peter Bühlmann

On MSE-optimal crossover designs

Christoph Neumann and Joachim Kunert

Testing for periodicity in functional time series

Siegfried Hörmann, Piotr Kokoszka, and Gilles Nisol

Limiting Behavior of Eigenvalues in High-dimensional MANOVA via RMT

Zhidong Bai, Kwok-Pui Choi, and Yasunori Fujikoshi

Two-sample Kolmogorov-Smirnov type tests revisited: Old and new tests in terms of local levels

Helmut Finner and Veronika Gontscharuk

Robust Gaussian Stochastic Process Emulation

Mengyang Gu, Xiaojing Wang, and Jim Berger

Convergence of contrastive divergence algorithm in exponential family

Bai Jiang, Tung-Yu Wu, Yifan Jin, and Wing Hung Wong

Combinatorial Inference for Graphical Models

Matey Neykov, Junwei Lu, and Han Liu

Overcoming the Limitations of Phase Transition by Higher Order Analysis of Regularization Techniques

Haolei Weng, Arian Maleki, and Le Zheng

Estimation and Prediction using generalized Wendland Covariance Functions under fixed domain asymptotics

Moreno Bevilacqua, Tarik Faouzi, Reinhard Furrer, and Emilio Porcu

Optimal adaptive estimation of linear functionals under sparsity

Olivier Collier, Laetitia Comminges, Alexandre Tsybakov, and Nicolas Verzelen

High-dimensional consistency in score-based and hybrid structure learning

Preetam Nandy, Alain Hauser, and Marloes H. Maathuis

A New Scope of Penalized Empirical Likelihood with High-Dimensional Estimating Equations

Jinyuang Chang, Cheng Yong Tang, and Tong Tong Wu

Approximate ℓ0-penalized estimation of piecewise-constant signals on graphs

Zhou Fan and Leying Guan

Information Measures, Experiments, Multi-category Hypothesis Tests, and Surrogate Losses

John C Duchi, Khashayar Khosravi, and Feng Ruan

Halfspace depths for scatter, concentration and shape matrices

Davy Paindaveine and Germain Van Bever

Multilayer tensor factorization with applications to recommender systems

Xuan Bi, Annie Qu, and Xiaotong Shen

Principal Component Analysis for Functional Data on Riemannian Manifolds and Spheres

Xiongtao Dai and Hans-Georg Müller

Assessing Robustness of Classi fication using Angular Breakdown Point

Junlong Zhao, Guan Yu, and Yufeng Liu

Tail-greedy bottom-up data decompositions and fast multiple change-point detection

Piotr Fryzlewicz

ROCKET: Robust Confidence Intervals via Kendall's Tau for Transelliptical Graphical Models

Rina Foygel Barber and Mladen Kolar

Adaptive invariant density estimation for ergodic diffusions over anisotropic classes

Claudia Strauch

Chebyshev polynomials, moment matching, and optimal estimation of the unseen

Yihong Wu and Pengkun Yang

Robust Low-Rank Matrix Estimation

Andreas Elsener and Sara van de Geer

Sieve Bootstrap for Functional Time Series

Efstathios Paparoditis

Maximuim likelihood estimation in Gaussian models under total positivity

Steffen Lilholt Lauritzen, Caroline Uhler, and Piotr Zwiernik

Multiscale Scanning in Inverse Problems

Katharina Proksch, Frank Werner, and Axel Munk

Slope meets Lasso: Improved oracle bounds and optimality

Pierre C. Bellec, Guillaume Lecue, and Alexandre B. Tsybakov

Uniformly Valid Post-Regularization Confidence Regions for Many Functional Parameters in Z-Estimation Framework

Alexandre Belloni, Victor Chernozhukov, Denis Chetverikov, and Ying Wei

Local asymptotic equivalence of pure states ensembles and quantum Gaussian white noise

Cristina Butucea, Madalin Guta, and Michael Nussbaum

Extreme Quantile Treatment Effects

Yichong Zhang

Optimal maximin L1-distance Latin hypercube designs based on good lattice point designs

Lin Wang, Qian Xiao, and Hongquan Xu

Rho-Estimators Revisited: General Theory and Applications

Yannick Baraud and Lucien Birgé

Think globally, fit locally under the Manifold Setup: Asymptotic Analysis of Locally Linear Embedding

Hau-tieng Wu and Nan Wu

Nonparametric covariate-adjusted response-adaptive design based on a functional urn model

Giacomo Aletti, Andrea Ghiglietti, and William F. Rosenberger

Distribution theory for hierarchical processes

Federico Camerlenghi, Antonio Lijoi, Peter Orbanz, and Igor Pruenster

Restricted Strong Convexity Implies Weak Submodularity

Ethan R. Elenberg, Rajiv Khanna, Alexandros G. Dimakis, and Sahand Negahban

Adaptive Estimation of the Sparsity in the Gaussian Vector Model

Alexandra Carpentier and Nicolas Verzelen

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

Approximate Optimal Designs for Multivariate Polynomial Regression

Yohann De Castro, Fabrice Gamboa, Didier Henrion, Roxana Hess, and Jean-Bernard Lasserre

Efficient Estimation of Integrated Volatility Functionals via Multiscale Jackknife

Jia Li, Yunxiao Liu, and Dacheng Xiu

Non-Asymptotic Rates for Manifold, Tangent Space, and Curvature Estimation

Clément Levrard and Eddie Aamari

Nonparametric testing for multiple survival functions with non-inferiority margins

Hsin-wen Chang and Ian W. McKeague

Estimation in the convolution structure density model. Part I: oracle inequalities

Oleg Lepski and Thomas Willer

Efficient multivariate entropy estimation via k-nearest neighbour distances

Thomas Benjamin Berrett, Richard John Samworth, and Ming Yuan

Posterior Graph Selection and Estimation Consistency for High-Dimensional Bayesian Dag Models

Malay Ghosh, Kshitij Khare, and Xuan Cao

Locally adaptive confidence bands

Tim Patschkowski and Angelika Rohde

Asymptotic Distribution-Free Change-Point Detection for Multivariate and non-Euclidean Data

Lynna Chu and Hao Chen

Statistics on the (Compact) Stiefel Manifold: Theory and Applications

Rudrasis Chakraborty and Baba Vemuri

Goodness-of-fit tests for the functional linear model based on randomly projected empirical processes

Juan A. Cuesta-Albertos, Eduardo García-Portugués, Manuel Febrero-Bande, and Wenceslao González-Manteiga

Cross: Efficient Low-rank Tensor Completion

Anru Zhang

Convolved Subsampling Estimation with Applications to Block Bootstrap

Johannes Tewes, Daniel J. Nordman, and Dimitris N. Politis

Feature elimination in kernel machines in moderately high dimensions

Sayan Dasgupta, Yair Goldberg, and Michael R Kosorok

Testing in High-Dimensional Spiked Models

Iain M Johnstone and Alexei Onatski

Covariate balancing propensity score by tailored loss functions

Qingyuan Zhao

High-dimensional covariance matrices in elliptical distributions with application to spherical test

Jiang Hu, Weiming Li, Zhi Liu, and Wang Zhou

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