Papers to Appear in Subsequent Issues

Developments in the theory of shape constrained inference Piet Groeneboom and Geurt Jongbloed
Shape Constrained Density Estimation via Penalized Rényi Divergence Roger Koenker and Ivan Mizera
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
Limit theory in monotone function estimation Cecile Durot and Hendrik Lopuhaä
Nonparametric Shape-restricted Regression Adityanand Guntuboyina and Bodhisattva Sen
Recent progress in log-concave density estimation Richard John Samworth
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
Methods in Estimation of Convex Sets Victor-Emmanuel Brunel
A conversation with Jon Wellner Moulinath Banerjee and Richard J Samworth
A Framework for Estimation and Inference in Generalized Additive Models with Shape and Order Restrictions Mary C Meyer
Shape Constraints in Economics and Operations Research Andrew Luke Johnson and Daniel R Jiang
Editorial: Special issue on ‘Nonparametric inference under shape constraints’ Richard John Samworth and Bodhisattva Sen
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