Comparison of Two Methods for Calculating the Partition Functions of Various Spatial Statistical Models |
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| Authors: | Fuchun Huang,& Yosihiko Ogata |
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| Affiliation: | School of Computing and Mathematics, Deakin University, Australia,;Dept of Statistical Science, The Graduate University for Advanced Studies, Japan, and The Institute of Statistical Mathematics, Japan |
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| Abstract: | Likelihood computation in spatial statistics requires accurate and efficient calculation of the normalizing constant (i.e. partition function) of the Gibbs distribution of the model. Two available methods to calculate the normalizing constant by Markov chain Monte Carlo methods are compared by simulation experiments for an Ising model, a Gaussian Markov field model and a pairwise interaction point field model. |
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| Keywords: | Gibbs sampling likelihood MCMC integration Metropolis algorithm partition function. |
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