The Annals of Statistics

The Bayesian Bootstrap

Donald B. Rubin

Full-text: Open access

Abstract

The Bayesian bootstrap is the Bayesian analogue of the bootstrap. Instead of simulating the sampling distribution of a statistic estimating a parameter, the Bayesian bootstrap simulates the posterior distribution of the parameter; operationally and inferentially the methods are quite similar. Because both methods of drawing inferences are based on somewhat peculiar model assumptions and the resulting inferences are generally sensitive to these assumptions, neither method should be applied without some consideration of the reasonableness of these model assumptions. In this sense, neither method is a true bootstrap procedure yielding inferences unaided by external assumptions.

Article information

Source
Ann. Statist. Volume 9, Number 1 (1981), 130-134.

Dates
First available: 12 April 2007

Permanent link to this document
http://projecteuclid.org/euclid.aos/1176345338

JSTOR
links.jstor.org

Digital Object Identifier
doi:10.1214/aos/1176345338

Mathematical Reviews number (MathSciNet)
MR600538

Subjects
Primary: 62A15
Secondary: 62F15: Bayesian inference 62G05: Estimation

Keywords
Model-free inference Dirichlet jackknife

Citation

Rubin, Donald B. The Bayesian Bootstrap. The Annals of Statistics 9 (1981), no. 1, 130--134. doi:10.1214/aos/1176345338. http://projecteuclid.org/euclid.aos/1176345338.


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