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Convergence of posteriors for discretized log Gaussian Cox processes

In Markov chain Monte Carlo posterior computation for log Gaussian Cox processes (LGCPs) a discretization of the continuously indexed Gaussian field is required. It is demonstrated that approximate posterior expectations computed from discretized LGCPs converge to the exact posterior expectations when the cell sizes of the discretization tends to zero. The effect of discretization is studied in a data example.
Year of publication:
2004
Authors: Waagepetersen, Rasmus
Published in:
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 66.2004, 3, p. 229-235
Publisher: Elsevier
Keywords: Bayesian inference Discretization Log Gaussian Cox process Monte Carlo Point processes Posterior
Type of publication: Article
Source:
Persistent link: https://www.econbiz.de/10005223511
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