An almost unbiased Liu-type estimator in the linear regression model
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Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
A biased estimator, compared to least squares estimators, is one of the most used statistical procedures to overcome the problem of multicollinearity. Liu-type estimators, which are biased estimators, are preferred in a wide range of fields. In this article, we propose an almost unbiased Liu-type (AUNL) estimator and discuss its performance under the mean square error matrix criterion among existing estimators. The proposed AUNL estimator is a general estimator and is based on the function of a single biasing parameter. It includes an ordinary least squares estimator, an almost unbiased ridge estimator, an almost unbiased Liu estimator, and an almost unbiased two-parameter estimator. Finally, real data examples and a Monte Carlo simulation are provided to illustrate the theoretical results.
Açıklama
Anahtar Kelimeler
Almost unbiased Liu-type estimator; Biased estimation; Liu-type estimator; Mean squared error; Multicollinearity
Kaynak
Communications In Statistics-Simulation and Computation
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
53
Sayı
7
