Almost unbiased Liu-type estimators in gamma regression model
Küçük Resim Yok
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The Liu-type estimator has been consistently demonstrated to be an attractive shrinkage method to reduce the effect of multicollinearity problem. It is known that multicollinear-ity affects the variance of the maximum likelihood estimator negatively in gamma regression model. Therefore, an almost unbiased Liu-type estimator together with a modified version of it is proposed to overcome the multicollinearity problem. The performance of the new estimators is investigated both theoretically and numerically via a Monte Carlo simulation experiment and a real data illustration. Based on the results, it is observed that the proposed estimators can bring significant improvement relative to other competitor estimators. (c) 2021 Elsevier B.V. All rights reserved.
Açıklama
Anahtar Kelimeler
Almost Unbiased Liu Type Estimator, Gamma Regression, Liu Type Estimator, Multicollinearity, Modified Almost Unbiased Liu Type Estimator, Monte Carlo Simulation
Kaynak
Journal Of Computational And Applied Mathematics
WoS Q Değeri
Q1
Scopus Q Değeri
Q2
Cilt
403
