A moment-based criterion for determining the number of components in a normal mixture model

Determining the number of components is a crucial issue in a mixture model. A moment-based criterion is considered to estimate the number of components arising from a normal mixture model. This criterion is derived from an omnibus statistic involving the skewness and kurtosis of each component. The...

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Bibliographic Details
Published in:Journal of systems engineering and electronics 2017-08, Vol.28 (4), p.801-809
Main Authors: Yimin Zhou, Liyan Han, Dan Wang, Libo Yin
Format: Article
Language:English
Subjects:
components
criteria
Gaussian
information
mixture
momentbased
number
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Summary:Determining the number of components is a crucial issue in a mixture model. A moment-based criterion is considered to estimate the number of components arising from a normal mixture model. This criterion is derived from an omnibus statistic involving the skewness and kurtosis of each component. The proposed criterion additionally provides a measurement for the model fit in an absolute sense. The performances of our criterion are satisfactory compared with other classical criteria through Monte-Carlo experiments.
ISSN:1004-4132
DOI:10.21629/JSEE.2017.04.20