Bayesian estimation of generalized Gamma mixture model based on variational EM algorithm

•We propose a VEM algorithm for the inference of the generalized Gamma mixture model (GMM) with all the closed-form update equations.•The help function is used to approximate the lower bound of the variational objective function in GMM.•With the proposed VEM algorithm, the effective number of compon...

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Veröffentlicht in:	Pattern recognition Jg. 87; S. 269 - 284
Hauptverfasser:	Liu, Chi, Li, Heng-Chao, Fu, Kun, Zhang, Fan, Datcu, Mihai, Emery, William J.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.03.2019
Schlagworte:	Extended factorized approximation Finite mixture models Generalized Gamma distribution Maximum likelihood estimation Variational expectation-maximization (VEM) Maximum likelihood estimation Finite mixture models Generalized Gamma distribution Extended factorized approximation Variational expectation-maximization (VEM)
ISSN:	0031-3203, 1873-5142
Online-Zugang:	Volltext
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