Parameter estimation with profile likelihood method and penalized EM algorithm in normal mixture distributions

AÇIKGÖZ İ.

JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS, cilt.21, sa.7, ss.1211-1228, 2018 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 21 Sayı: 7
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1080/09720510.2018.1496520
  • Dergi Adı: JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI)
  • Sayfa Sayıları: ss.1211-1228
  • Anahtar Kelimeler: Normal mixture distribution, EM algorithm, Penalized EM algorithm, Profile likelihood method, Estimation of parameter, MAXIMUM-LIKELIHOOD
  • Ankara Üniversitesi Adresli: Evet

Özet

As we know, as the likelihood function of the normal mixture is not a bounded function on Theta, a global maximum likelihood estimation(MLE) can not always be found and use of an EM (Expectation-Maximization) algorithm can possible lead towards a degenerate solution.