Comparisons of some weighted mixed biased estimators for the linear regression model

KARAPINAR D., Polat M., ÖZBAY N., KAÇIRANLAR S.

TURKISH JOURNAL OF MATHEMATICS, vol.50, no.3, pp.539-554, 2026 (SCI-Expanded, Scopus, TRDizin) identifier

  • Publication Type: Article / Article
  • Volume: 50 Issue: 3
  • Publication Date: 2026
  • Doi Number: 10.55730/1300-0098.3667
  • Journal Name: TURKISH JOURNAL OF MATHEMATICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, MathSciNet, zbMATH, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.539-554
  • Karadeniz Technical University Affiliated: Yes

Abstract

This paper presents comparative results on the two-parameter weighted mixed estimator, which is a distinct class of estimator defined to address the problem of multicollinearity. The two-parameter weighted mixed estimator is a general estimator that includes the weighted mixed estimator, the weighted mixed Liu estimator, and the weighted mixed ridge estimator. Detailed comparisons among the mentioned estimators are carried out based on the matrix mean square error. Theoretical findings are supported by two numerical examples in addition to a Monte Carlo simulation study.