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A novel mixture model using the multivariate normal mean-variance mixture of Birnbaum-Saunders distributions and its application to extrasolar planets. (English) Zbl 1417.62176

Summary: This paper presents a new finite mixture model based on the multivariate normal mean-variance mixture of Birnbaum-Saunders (NMVBS) distribution. We develop a computationally analytical EM algorithm for model fitting. Due to the dependence of this algorithm on initial values and the number of mixing components, a learning-based EM algorithm and an extended variant are proposed. Numerical simulations show that the proposed algorithms allow for better clustering performance and classification accuracy than some competing approaches. The effectiveness and prominence of the proposed methodology are also shown through an application to an extrasolar planet dataset.

MSC:

62H30 Classification and discrimination; cluster analysis (statistical aspects)
62E15 Exact distribution theory in statistics
62P35 Applications of statistics to physics
85A05 Galactic and stellar dynamics
85A35 Statistical astronomy

Software:

QRM; CensMixReg
PDFBibTeX XMLCite
Full Text: DOI

References:

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