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dec 1999 Bayesian smoothing in the estimation of the pair potential function of Gibbs point processes
Juha Heikkinen, Antti Penttinen
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Bernoulli 5(6): 1119-1136 (dec 1999).

Abstract

A flexible Bayesian method is suggested for the pair potential estimation with a high-dimensional parameter space. The method is based on a Bayesian smoothing technique, commonly applied in statistical image analysis. For the calculation of the posterior mode estimator a new Monte Carlo algorithm is developed. The method is illustrated through examples with both real and simulated data, and its extension into truly nonparametric pair potential estimation is discussed.

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Juha Heikkinen. Antti Penttinen. "Bayesian smoothing in the estimation of the pair potential function of Gibbs point processes." Bernoulli 5 (6) 1119 - 1136, dec 1999.

Information

Published: dec 1999
First available in Project Euclid: 23 March 2006

zbMATH: 0954.62035
MathSciNet: MR1735787

Keywords: Bayesian smoothing , Gibbs processes , Markov chain Monte Carlo methods , Marquardt algorithm , pair potential function , posterior mode estimator

Rights: Copyright © 1999 Bernoulli Society for Mathematical Statistics and Probability

Vol.5 • No. 6 • dec 1999
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