A new R package for Bayesian estimation of multivariate normal mixtures allowing for selection of the number of components and interval-censored data

Computational Statistics and Data Analysis

Volumn 53, Issue 12, 2009, Pages 3932-3947

  Komárek, Arnošt ^a  

^a CHARLES UNIVERSITY   (Czech Republic)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN ESTIMATIONS; CENSORED DATA; CENSORED OBSERVATIONS; COMPUTATIONAL SPEED; ESTIMATED MODEL; INFORMATION CRITERION; JOINT ESTIMATION; MARKOV CHAIN MONTE CARLO; MIXTURE COMPONENTS; MULTIVARIATE NORMAL; NORMAL MIXTURES; NUMBER OF COMPONENTS; PREDICTIVE DENSITY; REAL EXAMPLE; REVERSIBLE JUMP MCMC; SEMIPARAMETRIC DENSITY ESTIMATION; SUMMARY STATISTIC; UNIVARIATE;

BAYESIAN NETWORKS; DATA REDUCTION; MARKOV PROCESSES; PARAMETER ESTIMATION;

MIXTURES;

EID: 69449085475     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2009.05.006     Document Type: Article

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