On thinning of chains in MCMC

Methods in Ecology and Evolution
By:  and 



1. Markov chain Monte Carlo (MCMC) is a simulation technique that has revolutionised the analysis of ecological data, allowing the fitting of complex models in a Bayesian framework. Since 2001, there have been nearly 200 papers using MCMC in publications of the Ecological Society of America and the British Ecological Society, including more than 75 in the journal Ecology and 35 in the Journal of Applied Ecology.

2. We have noted that many authors routinely 'thin' their simulations, discarding all but every kth sampled value; of the studies we surveyed with details on MCMC implementation, 40% reported thinning.

3. Thinning is often unnecessary and always inefficient, reducing the precision with which features of the Markov chain are summarised. The inefficiency of thinning MCMC output has been known since the early 1990's, long before MCMC appeared in ecological publications.

4. We discuss the background and prevalence of thinning, illustrate its consequences, discuss circumstances when it might be regarded as a reasonable option and recommend against routine thinning of chains unless necessitated by computer memory limitations.

Publication type Article
Publication Subtype Journal Article
Title On thinning of chains in MCMC
Series title Methods in Ecology and Evolution
DOI 10.1111/j.2041-210X.2011.00131.x
Volume 3
Issue 1
Year Published 2012
Language English
Publisher British Ecological Society
Publisher location London, England
Contributing office(s) Patuxent Wildlife Research Center
Description 4 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Methods in Ecology and Evolution
First page 112
Last page 115
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