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Papers to Appear in Subsequent Issues

Graph connection laplacian methods can be made robust to noise

Noureddine El Karoui and Hau-tieng Wu

Efficient Calibration for Imperfect Computer Models

Rui Tuo and Jeff Wu

Functional Linear Regression with Points of Impact

Alois Kneip, Dominik Poss, and Pascal Sarda

Correction Inverse Regression for Longitudinal Data

Ci-Ren Jiang and Jane-Ling Wang

Optimal Detection of Multi-Sample Aligned Sparse Signals

Hock Peng Chan and Guenther Walther

Asymptotic Theory for Density Ridges

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

Fused Kernel-Spline Smoothing for Repeatedly Measured Outcomes in a Generalized Partially Linear Model with Functional Single Index

Fei Jiang, Yanyuan Ma, and Yuanjia Wang

Fully Adaptive Density-Based Clustering

Ingo Steinwart

Minimax Estimation in Sparse Canonical Correlation Analysis

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

Bayesian T-optimal discriminating designs

Holger Dette, Viatcheslav Melas, and Roman Guchenko

Bayesian linear regression with sparse priors

Ismael Castillo, Johannes Schmidt-Hieber, and Aad van der Vaart

Nonparametric confidence intervals for monotone functions

Piet Groeneboom and Geurt Jongbloed

A General Bernstein--von Mises Theorem in semiparametric models

Ismael Castillo and Judith Rousseau

Controlling the False Discovery Rate via Knockoffs

Rina Foygel Barber and Emmanuel Candes

Subsampling Bootstrap of Count Features of Networks

Sharmodeep Bhattacharyya and Peter J Bickel

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

Adaptive Testing on a Regression Function at a Point

Timothy Armstrong

Asymptotics in directed exponential random graph models with an increasing bi-degree sequence

Ting Yan, Chenlei Leng, and Ji Zhu

Estimation and inference in generalized additive coefficient models for nonlinear interactions with high-dimensional covariates

Shujie Ma, Raymond J Carroll, Hua Liang, and Shizhong Xu

Aggregation of predictors for non stationary sub-linear processes and online adaptive forecasting of time varying autoregressive processes

Andres Sanchez-Perez, François Roueff, and Christophe Giraud

Functional Additive Regression

Yingying Fan, Gareth James, and Peter Radchenko

Simultaneous confidence bands for change point tests in high dimension

Moritz Jirak

Coupling methods for multistage sampling

Guillaume Chauvet

Near-optimal estimation of jump activity in semimartingales

Adam David Bull

Empirical risk minimization for heavy-tailed losses

Gabor Lugosi, Christian Brownlees, and Emilien Joly

Bootstrap and permutation tests of independence for point processes

Mélisande Albert, Yann Bouret, Magalie Fromont, and Patricia Reynaud-Bouret

Optimal Experimental Designs for fMRI via Circulant Biased Weighing Designs

Ming-Hung Kao and Ching-Shui Cheng

Spectral statistics of large dimensional Spearman's rank correlation matrix and its application

Zhigang Bao, Liang-Ching Lin, Guangming Pan, and Wang Zhou

Rate-optimal Graphon Estimation

Gao Chao, Yu Lu, and Harrison Zhou

Bootstrap confidence sets under model misspecification

Vladimir Spokoiny and Mayya Zhilova

Model Selection and Structure Specification in Ultra-High Dimensional Generalised Semi-Varying Coefficient Models

Degui Li, Yuan Ke, and Wenyang Zhang

Estimation of Functionals of Sparse Covariance Matrices

Jianqing Fan, Philippe Rigollet, and Weichen Wang

Inference using noisy degrees - Differentially private beta model and synthetic graphs

Vishesh Karwa and Aleksandra Slavkovic

Bridging centrality and extremity: refining empirical data depth using extreme value statistics

John H.J. Einmahl, Jun Li, and Regina Y. Liu

Optimization via Low-rank Approximation for Community Detection in Networks

Can M. Le, Elizaveta Levina, and Roman Vershynin

Optimal designs in regression with correlated errors

Holger Dette, Andrey Pepelyshev, and Anatoly Zhigljavsky

Asymptotics for change-point models under varying degrees of mis-specification

Rui Song, Moulinath Banerjee, and Michael Kosorok

Functional data analysis for density functions by transformation to a Hilbert space

Alexander Petersen and Hans-Georg Müller

Projected Principal Component Analysis in Factor Models

Jianqing Fan, Yuan Liao, and Weichen Wang

Estimating the Smoothness of a Gaussian Random Field from Irregularly Spaced Data Via Higher-Order Quadratic Variations

Wei-Liem Loh

Adaptation to lowest density regions with application to support recovery

Tim Patschkowski and Angelika Rohde

Additive Partially Linear Quantile Regression in Ultra-high Dimension

Ben Sherwood and Lan Wang

Adaptive Bayesian Estimation via Block Prior

Chao Gao and Harrison Zhou

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

Tengyao Wang, Quentin Berthet, and Richard John Samworth

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