Christensen, O. F. and Møller, J. and Waagepetersen, R. P. (2001) Geometric ergodicity of Metropolis-Hastings algorithms for conditional simulation in generalised linear mixed models. Methodology and computing in applied probability, 3 (3). pp. 309-327. ISSN 1387-5841Full text not available from this repository.
Conditional simulation is useful in connection with inference and prediction for a generalized linear mixed model. We consider random walk Metropolis and Langevin-Hastings algorithms for simulating the random effects given the observed data, when the joint distribution of the unobserved random effects is multivariate Gaussian. In particular we study the desirable property of geometric ergodicity, which ensures the validity of central limit theorems for Monte Carlo estimates.
|Journal or Publication Title:||Methodology and computing in applied probability|
|Uncontrolled Keywords:||conditional simulation - generalized linear mixed model - geometric ergodicity - Langevin-Hastings algorithm - Markov chain Monte Carlo - random walk Metropolis algorithm|
|Subjects:||Q Science > QA Mathematics|
|Departments:||Faculty of Science and Technology > Mathematics and Statistics|
|Deposited On:||18 Nov 2008 15:27|
|Last Modified:||26 Jul 2012 15:28|
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