Papers to Appear in Subsequent Issues

Sparse regression: Scalable algorithms and empirical performance Dimitris Bertsimas, Jean Pauphilet, and Bart Van Parys
Convex Relaxation Methods for Community Detection Xiaodong Li, Yudong Chen, and Jiaming Xu
Best Subset, Forward Stepwise, or Lasso? Analysis and Recommendations Based on Extensive Comparisons Trevor hastie, Robert Tibshirani, and Ryan Tibshirani
Minimax Rates in Network Analysis: Graphon Estimation, Community Detection and Hypothesis Testing Chao Gao and Zongming Ma
Exponential-Family Models of Random Graphs: Inference in Finite-, Super-, and Infinite-Population Scenarios Michael Schweinberger, Pavel N. Krivitsky, Carter T. Butts, and Jonathan Stewart
Bipartite Causal Inference with Interference Corwin M Zigler and Georgia Papadogeorgou
A general framework for Vecchia approximations of Gaussian processes Matthias Katzfuss and Joseph Guinness
Additive and multiplicative effects network models Peter Hoff
A Unified Primal Dual Active Set Algorithm for Nonconvex Sparse Recovery Jian Huang, Yuling Jiao, Bangti Jin, Jin Liu, Xiliang Lu, and Can Yang
A statistical framework for modern network science Harry Crane and Walter Dempsey
Judicious Judgment Meets Unsettling Updating: Dilation, Sure Loss, and Simpson’s Paradox Ruobin Gong and Xiao-Li Meng
A Conversation with J. Stuart (Stu) Hunter Richard D. De Veaux
On general notions of depth for regression Yijun Zuo
A Conversation with Tze Leung Lai Zhiliang Ying, Dylan S. Small, and Ying Lu
The Box-Cox Transformation: Review and Extensions Anthony C Atkinson, Marco Riani, and Aldo Corbellini
Non-commutative Probability and Multiplicative Cascades Ian Wray McKeague
A selective overview of deep learning Jianqing Fan, Cong Ma, and Yiqiao Zhong
Stochastic Approximation: from Statistical Origin to Big-Data, Multidisciplinary Applications Tze Leung Lai and Hongsong Yuan
Robust high dimensional factor models with applications to statistical machine learning Jianqing Fan, Kaizheng Wang, Yiqiao Zhong, and Ziwei Zhu
On estimation and inference in latent structure random graphs Avanti Athreya, Minh Tang, Youngser Park, and Carey E. Priebe
A Hybrid Scan Gibbs Sampler for Bayesian Models with Latent Variables Grant Backlund, James P Hobert, Yeun Ji Jung, and Kshitij Khare
Network Modeling in Biology: Statistical Methods for Gene and Brain Networks Y.X. Rachel Wang, Lexin Li, Jingyi Jessica Li, and Haiyan Huang
Maximum likelihood multiple imputation: Faster imputations and consistent standard errors without posterior draws Paul T von Hippel and Jonathan Bartlett
A horse race between the block maxima method and the peak-over-threshold approach Axel Buecher and Chen Zhou
Khinchin’s 1929 paper on von Mises’s frequency theory of probability Lukas M. Verburgt
Random-Matrix Theory and Its Applications Alan Julian Izenman
A Conversation with Dennis Cook Efstathia Bura, Daniel Pena, Lexin Li, Christopher Nachtsheim, Claude Setodji, Robert E Weiss, and Bing Li
The GENIUS Approach to Robust Mendelian Randomization Inference Eric Tchetgen Tchetgen, BaoLuo Sun, and Stefan Walter
A general framework for the analysis of adaptive experiments Ian C. Marschner
A Problem in Forensic Science Highlighting the Differences between the Bayes Factor and Likelihood Ratio Danica M Ommen  and Christopher P. Saunders
A Discussion on Practical Considerations with Sparse Regression Methodologies Owais Sarwar, Benjamin Sauk, and Nikolaos Sahinidis
Discussion of Hastie et al Rahul Mazumder
Modern Variable Selection in Action:  Comment on the Papers by HTT and BPV Edward I. George
Discussion on: Sparse regression: Scalable algorithms and empirical performance & Best Subset, Forward Stepwise, or Lasso? Analysis and recommendations based on extensive comparisons Yuansi Chen, Armeen Taeb, and Peter Bühlmann
Identification of Causal Effects Within Principal Strata Using an Auxiliary Variable Peng Deng
Confidence as likelihood Yudi Pawitan and Youngjo Lee
Rejoinder: Best Subset, Forward Stepwise, or Lasso? Rob Tibshirani