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Stein’s Method Meets Computational Statistics: A Review of Some Recent Developments

Lookup NU author(s): Professor Chris Oates

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Abstract

© Institute of Mathematical Statistics, 2023Stein’s method compares probability distributions through the study of a class of linear operators called Stein operators.While mainly studied in probability and used to underpin theoretical statistics, Stein’s method has led to significant advances in computational statistics in recent years. The goal of this survey is to bring together some of these recent developments, and in doing so, to stimulate further research into the successful field of Stein’s method and statistics. The topics we discuss include tools to benchmark and compare sampling methods such as approximate Markov chain Monte Carlo, deterministic alternatives to sampling methods, control variate techniques, parameter estimation and goodness-of-fit testing

Publication metadata

Author(s): Anastasiou A, Barp A, Briol F-X, Ebner B, Gaunt RE, Ghaderinezhad F, Gorham J, Gretton A, Ley C, Liu Q, Mackey L, Oates CJ, Reinert G, Swan Y

Publication type: Article

Publication status: Published

Journal: Statistical Science

Year: 2023

Volume: 38

Issue: 1

Pages: 120-139

Online publication date: 01/02/2023

Acceptance date: 28/10/2022

ISSN (print): 0883-4237

ISSN (electronic): 2168-8745

Publisher: Institute of Mathematical Statistics

URL: https://doi.org/10.1214/22-STS863

DOI: 10.1214/22-STS863

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