Limit theorems for maximum likelihood estimators in the Curie-Weiss-Potts model

Richard S. Ellis and Kongming Wang

Stochastic Processes and their Applications, 1992, vol. 40, issue 2, 251-288

Abstract: The Curie-Weiss-Potts model, a model in statistical mechanics, is parametrized by the inverse temperature [beta] and the external magnetic field h. This paper studies the asymptotic behavior of the maximum likelihood estimator of the parameter [beta] when h = 0 and the asymptotic behavior of the maximum likelihood estimator of the parameter h when [beta] is known and the true value of h is 0. The limits of these maximum likelihood estimators reflect the phase transition in the model; i.e., different limits depending on whether [beta] [beta]c, where [beta]c [epsilon] (0, [infinity]) is the critical inverse temperature of the model.

Keywords: maximum; likelihood; estimator; Curie-Weiss-Potts; model; empirical; vector (search for similar items in EconPapers)
Date: 1992
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Citations: View citations in EconPapers (3)

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