ESTIMATION IN MULTIFACTOR POLYNOMIAL REGRESSION UNDER NON-NORMALITY

Tiku M. L., Akkaya A.

PAKISTAN JOURNAL OF STATISTICS, cilt.26, sa.1, ss.49-68, 2010 (SCI-Expanded) identifier

  • 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.