Berthelsen, Kasper K.; Breyer, Laird A.; Roberts, Gareth O. Perfect posterior simulation for mixture and hidden Markov models. (English) Zbl 1226.60100 LMS J. Comput. Math. 13, 246-259 (2010). Summary: We present an application of the read-once coupling from the past algorithm to problems in Bayesian inference for latent statistical models. We describe a method for perfect simulation from the posterior distribution of the unknown mixture weights in a mixture model. Our method is extended to a more general mixture problem, where unknown parameters exist for the mixture components, and to a hidden Markov model. MSC: 60J22 Computational methods in Markov chains 62F12 Asymptotic properties of parametric estimators 62F15 Bayesian inference Keywords:coupling from the past; Bayesian inference; general mixture problem; hidden Markov model PDFBibTeX XMLCite \textit{K. K. Berthelsen} et al., LMS J. Comput. Math. 13, 246--259 (2010; Zbl 1226.60100) Full Text: DOI References: [1] Diebolt, J. Roy. Statist. Soc. Ser. B 56 pp 363– (1994) This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.