Papers to Appear in Subsequent Issues

Probabilistic Integration: A Role in Statistical Computation? Francois-Xavier Briol, Chris Oates, Mark Girolami, Michael Osborne, and Dino Sejdinovic
Gaussian integrals and Rice series in crossing distributions – to compute the distribution of maxima and other features of Gaussian processes Georg Lindgren
A Conversation with Piet Groeneboom Geurt Jongbloed
Automated  versus  do-it-yourself methods  for  causal  inference: Lessons  learned  from  a  data analysis  competition Vincent Dorie, Jennifer Hill, Uri Shalit, Marc Scott, and Dan Cervone
Generalized Multiple Importance Sampling Víctor Elvira, Luca Martino, David Luengo, and Mónica F. Bugallo
Bayes, Oracle Bayes, and Empirical Bayes Bradley Efron
A kernel regression procedure in the 3D shape space with an application to online sales of children’s wear Gregorio Quintana-Orti and Amelia Simó
Unreasonable effectiveness of Monte Carlo Art B Owen
Comment Michael L Stein and Ying Hung
A Conversation with Dick Dudley Vladimir Koltchinskii, Richard Nickl, and Philippe Rigollet
Causal Inference Competitions: Where Should We Aim? Ehud Karavani, Tal El-Hay, Yishai Shimoni, and Chen Yanover
Will competition-winning methods for causal inference also succeed in practice? Qingyuan Zhao, Luke Keele, and Dylan Small
Statistical Analysis of Zero-inflated Non-negative Continuous Data: a Review Lei Liu, Ya-Chen Tina Shih, Robert L. Strawderman, Daowen Zhang, Bankole Johnson, and Haitao Chai
Contributions of model features to BART causal inference performance using ACIC 2016 competition data Nicole Bohme Carnegie
Rejoinder for “Probabilistic Integration: A Role in Statistical Computation?” Francois-Xavier Briol, Chris J. Oates, Mark Girolami, Michael A. Osborne, and Dino Sejdinovic
Spherical cows in a vacuum: Data analysis competitions for causal inference Miguel Hernan
Comment on “Probabilistic Integration: A Role in Statistical Computation?” Fred J Hickernell and R. Jagadeeswaran