FINITE MIXTURES OF MULTIVARIATE SKEW LAPLACE DISTRIBUTIONS

DOĞRU F. Z., BULUT Y. M., ARSLAN O.

REVSTAT-STATISTICAL JOURNAL, cilt.19, sa.1, ss.35-46, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 19 Sayı: 1
  • Basım Tarihi: 2021
  • Dergi Adı: REVSTAT-STATISTICAL JOURNAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, zbMATH
  • Sayfa Sayıları: ss.35-46
  • Anahtar Kelimeler: EM algorithm, ML estimation, multivariate mixture model, MSL
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

This paper proposes finite mixtures of multivariate skew Laplace distributions in order to model both skewness and heavy-tailedness in heterogeneous data sets. Maximum likelihood estimators for the parameters of interest are obtained using the EM algorithm. The paper offers a small simulation study and a real data example to illustrate the performance of the proposed mixture model.