Bayesian Analysis

Frequentist Bayes is objective (comment on articles by Berger and by Goldstein)

Larry Wasserman

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Abstract

In this comment, I argue that Bayes procedures with good frequentist properties are objective. I introduce the idea with a short play, followed by some commentary.

Article information

Source
Bayesian Anal. Volume 1, Number 3 (2006), 451-456.

Dates
First available in Project Euclid: 22 June 2012

Permanent link to this document
https://projecteuclid.org/euclid.ba/1340371044

Digital Object Identifier
doi:10.1214/06-BA116H

Mathematical Reviews number (MathSciNet)
MR2221280

Zentralblatt MATH identifier
1331.62054

Keywords
coverage frequency probability objective Bayesian inference

Citation

Wasserman, Larry. Frequentist Bayes is objective (comment on articles by Berger and by Goldstein). Bayesian Anal. 1 (2006), no. 3, 451--456. doi:10.1214/06-BA116H. https://projecteuclid.org/euclid.ba/1340371044


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References

  • Genovese, C., Roeder, K., and Wasserman, L. (2005). "False discovery control with p-value weighting." Technical report, Carnegie Mellon University.
  • Mandelkern, M. (2002). "Setting confidence intervals for bounded parameters." Statistical Science, 17: 149–172.
  • Ming, L. and Vitany, P. (1997). An Introduction to Kolmogorov Complexity and Its Applications. New York: Springer.
  • Wasserman, L. (2002). "Comment on Mandelkern." Statistical Science, 17: 163.

See also

  • Related item: James Berger. The case for objective Bayesian analysis. Bayesian Anal., Vol. 1, Iss. 3 (2006), 385-402.
  • Related item: Michael Goldstein. Subjective Bayesian Analysis: Principles and Practice. Bayesian Anal., Vol. 1, Iss. 3 (2006), 403-420.