NDLI: The Bootstrap and Markov-Chain Monte Carlo

Content Provider	Scilit
Author	Efron, Bradley
Copyright Year	2011
Description	This note concerns the use of parametric bootstrap sampling to carry out Bayesian inference calculations. This is only possible in a subset of those problems amenable to Markov-Chain Monte Carlo (MCMC) analysis, but when feasible the bootstrap approach offers both computational and theoretical advantages. The discussion here is in terms of a simple example, with no attempt at a general analysis.
Related Links	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3203753/pdf
Ending Page	1062
Page Count	11
Starting Page	1052
ISSN	10543406
e-ISSN	15205711
DOI	10.1080/10543406.2011.607736
Journal	Journal of Biopharmaceutical Statistics
Issue Number	6
Volume Number	21
Language	English
Publisher	Informa UK Limited
Publisher Date	2011-10-24
Access Restriction	Open
Subject Keyword	Mathematical Social Sciences Statistics and Probability Bayes Credible Intervals Gibbs Sampling Importance Sampling
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Pharmacology Pharmacology (medical)

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The Bootstrap and Markov-Chain Monte Carlo