Likelihood and non-parametric Bayesian MCMC inference for spatial point processes based on perfect simulation and path sampling

Likelihood and non-parametric Bayesian MCMC inference for spatial point processes based on perfect simulation and path sampling (2003)

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by Kasper K. Berthelsen , Jesper Møller

Venue:	Scand. J. Statist
Citations:	10 - 3 self

BibTeX

@ARTICLE{Berthelsen03likelihoodand,
    author = {Kasper K. Berthelsen and Jesper Møller},
    title = {Likelihood and non-parametric Bayesian MCMC inference for spatial point processes based on perfect simulation and path sampling},
    journal = {Scand. J. Statist},
    year = {2003},
    volume = {30},
    pages = {549--564}
}

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Abstract

We consider the combination of path sampling and perfect simulation in the context of both likelihood inference and non-parametric Bayesian inference for pairwise interaction point processes. Several empirical results based on simulations and analysis of a dataset are presented, and the merits of using perfect simulation are discussed.

Citations

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