ESTIMATION IN MULTIFACTOR POLYNOMIAL REGRESSION UNDER NON-NORMALITY
PAKISTAN JOURNAL OF STATISTICS, cilt.26, sa.1, ss.49-68, 2010 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 26 Sayı: 1
- Basım Tarihi: 2010
- Dergi Adı: PAKISTAN JOURNAL OF STATISTICS
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.49-68
- Anahtar Kelimeler: Non-normality, Maximum likelihood, Modified maximum likelihood, Robustness, Polynomial regression, Outliers, Inliers, MAXIMUM-LIKELIHOOD, ROBUST ESTIMATION, DISTRIBUTIONS, PARAMETERS, MODEL, IDENTIFICATION, LOCATION
- Orta Doğu Teknik Üniversitesi Adresli: Evet
Özet
Modified maximum likelihood estimators of the parameters in a second order polynomial regression model are derived. They are shown to be considerably more efficient and robust than the commonly used least squares estimators. Real life examples are given.