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

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