APPLICATION OF MML METHODOLOGY TO AN alpha-SERIES PROCESS WITH WEIBULL DISTRIBUTION
HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS, cilt.39, sa.3, ss.449-460, 2010 (SCI-Expanded, Scopus, TRDizin)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 39 Sayı: 3
- Basım Tarihi: 2010
- Dergi Adı: HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
- Sayfa Sayıları: ss.449-460
- Anahtar Kelimeler: alpha-series process, Modified likelihood, Nonparametric, Efficiency, Monte Carlo simulation, MAXIMUM-LIKELIHOOD, REGRESSION, PARAMETERS
- Ankara Üniversitesi Adresli: Evet
Özet
In an alpha-series process, explicit estimators of the parameters alpha, mu and sigma(2) are obtained by using the methodology of modified maximum likelihood (MML) when the distribution of the first occurrence time of an event is assumed to be Weibull. Monte Carlo simulations are performed to compare the efficiencies of the MML estimators with the corresponding nonparametric (NP) estimators. We also apply the MML methodology to two real life data sets to show the performance of the MML estimators compared to the NP estimators.