Quotation Frühwirth-Schnatter, Sylvia. 2001. Fully Bayesian analysis of switching Gaussian state space models. Annals of the Institute of Statistical Mathematics 53, 31-49.


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Abstract

In the present paper we study switching state space models from a Bayesian point of view. For estimation, the model is reformulated as a hierarchical model. We discuss various MCMC methods for Bayesian estimation, among them unconstrained Gibbs sampling, constrained sampling and permutation sampling. We address in detail the problem of unidentifiability, and discuss potential information available from an unidentified model. Furthermore the paper discusses issues in model selection such as selecting the number of states or testing for the presence of Markov switching heterogeneity. The model likelihoods of all possible hypotheses are estimated by using the method of bridge sampling. We conclude the paper with applications to simulated data as well as to modelling the U.S./U.K. real exchange rate. (author's abstract)

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Annals of the Institute of Statistical Mathematics
Citation Index SCI
WU-Journal-Rating new FIN-A, VW-D
Language English
Title Fully Bayesian analysis of switching Gaussian state space models
Volume 53,
Year 2001
Page from 31
Page to 49
URL http://epub2.wu.ac.at/dyn/virlib/wp/eng/mediate/epub-wu-01_a43.pdf?ID=epub-wu-01_a43

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People
Frühwirth-Schnatter, Sylvia (Details)
Organization
Institute for Statistics and Mathematics IN (Details)
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