Papers to Appear in Subsequent Issues

Bayesian Analysis of Rank Data with Covariates and Heterogeneous Rankers Xinran Li, Dingdong Yi, and Jun S. Liu
The Dependent Dirichlet Process and Related Models Fernando A. Quintana, Peter Mueller, Alejandro Jara, and Steven N. MacEachern
A comparative tour through the simulation algorithms for max-stable processes Marco Oesting and Kirstin Strokorb
Analyzing Stochastic Computer Models: A Review with Opportunities Evan Baker, Pierre Barbillon, Arindam Fadikar, Robert Gramacy, Radu Herbei, David Higdon, Jiangeng Huang, Leah Johnson, Pulong Ma, Anirban Mondal, Bianica Pires, Jerome Sacks, and Vadim Sokolov
Statistical dependence: Beyond Pearson’s ρ Dag Tjøstheim, Håkon Otneim, and Bård Støve
Inference and asymptotics in high and low dimensional regimes Heather Battey and David Cox
Diffusion Smoothing for Spatial Point Patterns Adrian Baddeley, Tilman M. Davies, Suman Rakshit, Gopalan Nair, and Greg McSwiggan
Gambler’s Ruin and the ICM Persi Diaconis and Stewart N Ethier
Choosing Among Notions of Multivariate Depth Statistics Karl Mosler and Pavlo Mozharovskyi
Power Calculations for Replication Studies Charlotte Micheloud and Leonhard Held
A Conversation with Ross Prentice Li Hsu and Charles Kooperberg
Intention-To-Treat Comparisons in Randomized Trials Ross L Prentice and Aaron K Aragaki
Modeling the occurrence of events subject to a reporting delay via an EM algorithm Roel Verbelen, Katrien Antonio, Gerda Claeskens, and Jonas Crevecoeur
A Unifying Framework of  High-Dimensional Sparse Estimation with Difference-of-Convex (DC) Regularization Xiaoming Huo, Shanshan Cao, and Jong-Shi Pang
Interpreting P-values and Confidence Intervals using Well-Calibrated Null Preference Priors Michael P Fay, Michael A Proschan, Erica H Brittain, and Ram Tiwari
Measurement error models: from nonparametric methods to deep neural networks Zhirui Hu, Zheng Tracy Ke, and Jun S Liu
High-Performance Statistical Computing in the Computing Environments of the  2020s Seyoon Ko, Hua Zhou, Jin J. Zhou, and Joong-Ho Won
Statistical Aspects of the Quantum Supremacy Demonstration Yosef Rinott, Tomer Shoham, and Gil Kalai
Approximate Confidence Intervals for a Binomial p – Once Again Per Gösta Andersson
The SPDE Approach to Matérn Fields: Graph Representations Daniel Sanz-Alonso and Ruiyi Yang
The covariate-adjusted ROC curve: the concept and its importance, review of inferential methods, and a new Bayesian estimator Vanda Inácio and María Xosé Rodríguez-Álvarez
Challenges in Markov chain Monte Carlo for Bayesian neural networks Theodore Papamarkou, Jacob Hinkle, M. Todd Young, and David Womble
A Regression Perspective on Generalized Distance Covariance and the Hilbert-Schmidt Independence Criterion Dominic Edelmann and Jelle Goeman
Methods to Compute Prediction Intervals: A Review and New Results Qinglong Tian, Daniel J. Nordman, and William Q. Meeker
The costs and benefits of valid causal inference in the presence of high dimensional  nuisance parameters Niloofar Moosavi, Jenny Häggström, and Xavier de Luna
Confidence Intervals for Seroprevalence Joseph P Romano, Thomas J DiCiccio, David M Ritzwoller, and Azeem M Shaikh
A Conversation with Stephen Portnoy Xuming He and Xiaofeng Shao
Additive Bayesian variable selection under censoring and misspecification David Rossell
On some connections between Esscher’s tilting, saddlepoint approximations, and optimal transportation: a statistical perspective Davide Antonio La Vecchia, Elvezio Ronchetti, and Andrej Ilievski