Finite Mixtures of Matrix Variate t Distributions

Dogru F. Z., BULUT Y. M., ARSLAN O.

GAZI UNIVERSITY JOURNAL OF SCIENCE, cilt.29, sa.2, ss.335-341, 2016 (ESCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29 Sayı: 2
  • Basım Tarihi: 2016
  • Dergi Adı: GAZI UNIVERSITY JOURNAL OF SCIENCE
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus
  • Sayfa Sayıları: ss.335-341
  • Anahtar Kelimeler: Finite mixtures, matrix variate t, matrix variate normal, ML estimator, EM algorithm, MAXIMUM-LIKELIHOOD
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

Finite mixtures of multivariate t distributions (Peel and McLachlan (2000)) were introduced as an alternative to the finite mixtures of multivariate normal distributions to model data sets with heavy tails. In this study, we define the finite mixtures of matrix variate t distributions as an extension of finite mixtures of multivariate t distributions. Mixtures of matrix variate t distributions can provide an alternative robust model to the mixtures of matrix variate normal distributions (Viroli (2011)) for modeling matrix variate data sets with heavy tails. We give an Expectation Maximization (EM) algorithm to find the maximum likelihood (ML) estimators for the parameters of interest. We also provide a small simulation study to illustrate the performance of the proposed EM algorithm for finding estimates.