r - k Class estimator in the linear regression model with correlated errors

Siray G., KAÇIRANLAR S., SAKALLIOĞLU S.

STATISTICAL PAPERS, cilt.55, sa.2, ss.393-407, 2014 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 55 Sayı: 2
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1007/s00362-012-0484-8
  • Dergi Adı: STATISTICAL PAPERS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.393-407
  • Anahtar Kelimeler: Autocorrelation, Multicollinearity . r, k Class estimator, Ridge regression estimator, Mean square error matrix, PRINCIPAL COMPONENT REGRESSION, MEAN-SQUARE ERROR, RIDGE-REGRESSION, COMBINING RIDGE, PERFORMANCE
  • Çukurova Üniversitesi Adresli: Evet

Özet

Autocorrelation in errors and multicollinearity among the regressors are serious problems in regression analysis. The aim of this paper is to examine multicollinearity and autocorrelation problems concurrently and to compare the r - k class estimator to the generalized least squares estimator, the principal components regression estimator and the ridge regression estimator by the scalar and matrix mean square error criteria in the linear regression model with correlated errors.