Fast sampling of Gaussian Markov random fields
Håvard Rue Department of Mathematical Sciences, Norwegian University for Science and Technology, N‐7491 Trondheim, Norway. E-mail address: Havard.Rue@math.ntnu.no
Abstract
This paper demonstrates how Gaussian Markov random fields (conditional autoregressions) can be sampled quickly by using numerical techniques for sparse matrices. The algorithm is general and efficient, and expands easily to various forms for conditional simulation and evaluation of normalization constants. We demonstrate its use by constructing efficient block updates in Markov chain Monte Carlo algorithms for disease mapping.
Citing Literature
Number of times cited according to CrossRef: 170
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