Semi-Exact Control Functionals From Sard's Method
Abstract
The numerical approximation of posterior expected quantities of interest is considered. A novel control variate technique is proposed for post-processing of Markov chain Monte Carlo output, based both on Stein's method and an approach to numerical integration due to Sard. The resulting estimators are proven to be polynomially exact in the Gaussian context, while empirical results suggest the estimators approximate a Gaussian cubature method near the Bernstein-von-Mises limit. The main theoretical result establishes a bias-correction property in settings where the Markov chain does not leave the posterior invariant. Empirical results are presented across a selection of Bayesian inference tasks. All methods used in this paper are available in the R package ZVCV.
Cite
@article{arxiv.2002.00033,
title = {Semi-Exact Control Functionals From Sard's Method},
author = {Leah F. South and Toni Karvonen and Chris Nemeth and Mark Girolami and Chris. J. Oates},
journal= {arXiv preprint arXiv:2002.00033},
year = {2021}
}
Comments
There are 17 pages of main text. This revision provides an extended version of Theorem 1