title: Allocation Variable-Based Probabilistic Algorithm to Deal with Label Switching Problem in Bayesian Mixture Models.
abstract: The label switching problem occurs as a result of the nonidentifiability of posterior distribution over various permutations of component labels when using Bayesian approach to estimate parameters in mixture models. In the cases where the number of components is fixed and known, we propose a relabelling algorithm, an allocation variable-based (denoted by AVP) probabilistic relabelling approach, to deal with label switching problem. We establish a model for the posterior distribution of allocation variables with label switching phenomenon. The AVP algorithm stochastically relabel the posterior samples according to the posterior probabilities of the established model. Some existing deterministic and other probabilistic algorithms are compared with AVP algorithm in simulation studies, and the success of the proposed approach is demonstrated in simulation studies and a real dataset.
authors.affiliation: Department of Mathematics, National Chung Cheng University, Chiayi, Taiwan.
authors.forename: Jia-Chiun
authors.initials: JC
authors.lastname: Pan
authors.affiliation: Department of Psychiatry, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
authors.forename: Chih-Min
authors.initials: CM
authors.lastname: Liu
authors.affiliation: Department of Psychiatry, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
authors.forename: Hai-Gwo
authors.initials: HG
authors.lastname: Hwu
authors.affiliation: Institute of Statistics, National Chiao Tung University, Hsinchu, Taiwan.
authors.forename: Guan-Hua
authors.initials: GH
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D005260:Female; D006801:Humans; D008297:Male; D008490:Medical Informatics; D015233:Models, Statistical; D016012:Poisson Distribution; D011336:Probability; D012559:Schizophrenia / Q000453:epidemiology