A novel mixture model using the multivariate normal mean–variance mixture of Birnbaum–Saunders distributions and its application to extrasolar planets

Mehrdad Naderi, Wen-Liang Hung*, Tsung-I Lin, Ahad Jamalizadeh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)126-138
Number of pages3
JournalJournal of Multivariate Analysis
Volume171
Early online date14 Dec 2018
DOIs
Publication statusPublished - 1 May 2019
Externally publishedYes

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