Keeping the balance -- bridge sampling for marginal likelihood estimation in finite mixture, mixture of experts and Markov mixture models

DOI10.1214/19-BJPS446zbMath1499.62209MaRDI QIDQ2330483

Sylvia Frühwirth-Schnatter

Publication date: 22 October 2019

Published in: Brazilian Journal of Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.bjps/1566806429

zbMATH Keywords

importance samplingMarkov chain Monte Carlomodel-based clusteringGaussian mixtureshierarchical priorspermutation sampling

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Bayesian inference (62F15)

Related Items

Hidden Markov and semi-Markov models when and why are these models useful for classifying states in time series data? ⋮ Semiparametric finite mixture of regression models with Bayesian P-splines ⋮ Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence ⋮ Keeping the balance -- bridge sampling for marginal likelihood estimation in finite mixture, mixture of experts and Markov mixture models

Uses Software

• BayesLogit
• tsbridge
• bayesf

Cites Work

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