A quick procedure for model selection in the case of mixture of normal densities

DOI10.1016/J.CSDA.2007.05.023zbMath1445.62147OpenAlexW2047871829MaRDI QIDQ1020660

A. Durio E. D. Isaia

Publication date: 2 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.05.023

zbMATH Keywords

maximum likelihoodmultivariate Gaussian mixturessimulation studiesminimum integrated square errorMonte Carlo significance test

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Robustness and adaptive procedures (parametric inference) (62F35)

Cites Work

• Editorial: Recent developments in mixture models (Hamburg, July 2001)
• Estimating the number of components in a finite mixture model: the special case of homogeneity
• Editorial: Advances in mixture models
• Recent asymptotic results in testing for mixtures
• Statistical analysis of finite mixture distributions
• Robust and efficient estimation by minimising a density power divergence
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• Finite mixture models
• Mixture Models, Robustness, and the Weighted Likelihood Methodology
• Multivariate Normal Mixtures: A Fast Consistent Method of Moments
• Estimation in Mixtures of Two Normal Distributions
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