Regression diagnostics methods for Liu estimator under the general linear regression model

SÖKÜT AÇAR T., ÖZKALE ATICIOĞLU M. R.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, cilt.49, sa.3, ss.771-792, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 49 Sayı: 3
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1080/03610918.2019.1582781
  • Dergi Adı: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Business Source Elite, Business Source Premier, CAB Abstracts, Compendex, Computer & Applied Sciences, Veterinary Science Database, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.771-792
  • Anahtar Kelimeler: Leverages, Influence measure, Liu estimator, Autocorrelation, Multicollinearity
  • Çanakkale Onsekiz Mart Üniversitesi Adresli: Evet

Özet

This paper introduces the regression diagnostic methods for the Liu estimator under the general linear regression model with the autocorrelated error structure which is modeled by first-order autoregressive process. To identify the leverage observations, quasi-projection matrix is used, and to identify the influential observations DFFITS and Cook's D statistics which are single case deletion methods are used for the Liu estimator. For a special model with two explanatory variables, the leverage attitudes of the first observation are examined theoretically according to the autocorrelation coefficient and the Liu parameter. The proposed diagnostic methods are investigated through a numerical example.