Variance reduction in MCMC

We propose a general purpose variance reduction technique for MCMC estimators. The idea is obtained by combining standard variance reduction principles known for regular Monte Carlo simulations (Ripley, 1987) and the Zero-Variance principle introduced in the physics literature (Assaraf and Caffarel, 1999). The potential of the new idea is illustrated with some toy examples and an application to Bayesian estimation

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Year of publication:	2003-09
Authors:	Antonietta, Mira ; Paolo, Tenconi ; Dario, Bressanini
Institutions:	Facoltà di Economia, Università degli Studi dell'Insubria
Subject:	Markov chain Monte carlo \| Metropolis-Hastings algorithm \| Variance reduction \| Zero-Variance principle

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Extent:	application/pdf
Series:	Economics and Quantitative Methods.
Type of publication:	Book / Working Paper
Language:	English
Notes:	18 pages
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005612166