A Short History of Markov Chain Monte Carlo: Subjective Recollections from Incomplete Data

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Date
2011
Link to item file
http://hal.archives-ouvertes.fr/hal-00311793/en/
Dewey
Probabilités et mathématiques appliquées
Sujet
Metropolis-Hastings algorithm; simulation; Gibbs sampling; Monte Carlo
JEL code
C15
Journal issue
Statistical Science
Volume
26
Number
1
Publication date
2011
Article pages
102-115
Publisher
Institute of Mathematical Statistics
DOI
http://dx.doi.org/10.1214/10-STS351
URI
https://basepub.dauphine.fr/handle/123456789/3549
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Author
Casella, George
Robert, Christian P.
Type
Article accepté pour publication ou publié
Abstract (EN)
In this note we attempt to trace the history and development of Markov chain Monte Carlo (MCMC) from its early inception in the late 1940's through its use today. We see how the earlier stages of the Monte Carlo (MC, not MCMC) research have led to the algorithms currently in use. More importantly, we see how the development of this methodology has not only changed our solutions to problems, but has changed the way we think about problems.