Bayesian approach to thermostatistics
type: Item
instance of: scholarly article
title: Bayesian approach to thermostatistics
zbMATH Open document ID: 0645.62111
DOI: 10.1007/BF00669394
author: Bernard H. Lavenda
published in: International Journal of Theoretical Physics
publication date: 1988-01-01T00:00:00Z
review text: Bayes' theorem is used to derive the dual of the Gibbs formulation of statistical thermodynamics. An asymptotic analysis is performed, akin to Khinchin's use of the central limit theorem, to determine approximate expressions for the moment-generating functions. The prior densities, which are determined by equating the maximum-likelihood estimates with the moment expressions in the asymptotic limit, satisfy Jeffrey's invariant properties of improper prior densities.
Mathematics Subject Classification ID: 62P99
Mathematics Subject Classification ID: 62C10
Mathematics Subject Classification ID: 82B30
Mathematics Subject Classification ID: 62F15
zbMATH DE Number: 4052869
zbMATH Keywords: Bayes' theorem
zbMATH Keywords: asymptotic analysis
zbMATH Keywords: central limit theorem
zbMATH Keywords: approximate expressions
zbMATH Keywords: moment-generating functions
zbMATH Keywords: prior densities
zbMATH Keywords: maximum- likelihood estimates
zbMATH Keywords: Jeffrey's invariant properties of improper prior densities
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 4052869