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

Siray G., KAÇIRANLAR S., SAKALLIOĞLU S.

STATISTICAL PAPERS, vol.55, no.2, pp.393-407, 2014 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 55 Issue: 2
  • Publication Date: 2014
  • Doi Number: 10.1007/s00362-012-0484-8
  • Journal Name: STATISTICAL PAPERS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.393-407
  • Keywords: 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 University Affiliated: Yes

Abstract

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.