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Robust Markov chain Monte Carlo methods for spatial generalized linear mixed models

Christensen, OF ; Roberts, GO and Sköld, Martin LU (2006) In Journal of Computational and Graphical Statistics 15(1). p.1-17
Abstract
Using Markov chain Monte Carlo methods for statistical inference is often troublesome in practice, because performance of the algorithm may hugely depend on the observed data, and what works well for one dataset may fail miserably for another. In this article, for spatial generalized linear mixed models (GLMMs), we discuss problems with algorithms previously used, and we construct an algorithm with robust mixing and convergence characteristics, independent of the data. The strategy we have used for this construction is not model specific and could be applied in a much wider context.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
parameterization, spatial statistics
in
Journal of Computational and Graphical Statistics
volume
15
issue
1
pages
1 - 17
publisher
American Statistical Association
external identifiers
  • wos:000235953700001
  • scopus:33645558077
ISSN
1537-2715
DOI
10.1198/106186006X100470
language
English
LU publication?
yes
id
bbf261ed-be69-446b-a8ab-06b3bfe8292e (old id 416473)
date added to LUP
2016-04-01 12:22:20
date last changed
2020-01-12 09:42:53
@article{bbf261ed-be69-446b-a8ab-06b3bfe8292e,
  abstract     = {Using Markov chain Monte Carlo methods for statistical inference is often troublesome in practice, because performance of the algorithm may hugely depend on the observed data, and what works well for one dataset may fail miserably for another. In this article, for spatial generalized linear mixed models (GLMMs), we discuss problems with algorithms previously used, and we construct an algorithm with robust mixing and convergence characteristics, independent of the data. The strategy we have used for this construction is not model specific and could be applied in a much wider context.},
  author       = {Christensen, OF and Roberts, GO and Sköld, Martin},
  issn         = {1537-2715},
  language     = {eng},
  number       = {1},
  pages        = {1--17},
  publisher    = {American Statistical Association},
  series       = {Journal of Computational and Graphical Statistics},
  title        = {Robust Markov chain Monte Carlo methods for spatial generalized linear mixed models},
  url          = {http://dx.doi.org/10.1198/106186006X100470},
  doi          = {10.1198/106186006X100470},
  volume       = {15},
  year         = {2006},
}