An improved and efficient biased estimation technique in logistic regression model
Küçük Resim Yok
Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this article, we propose a new improved and efficient biased estimation method which is a modified restricted Liu-type estimator satisfying some sub-space linear restrictions in the binary logistic regression model. We study the properties of the new estimator under the mean squared error matrix criterion and our results show that under certain conditions the new estimator is superior to some other estimators. Moreover, a Monte Carlo simulation study is conducted to show the performance of the new estimator in the simulated mean squared error and predictive median squared errors sense. Finally, a real application is considered.
Açıklama
Anahtar Kelimeler
Restricted Maximum Likelihood Estimator, Restricted Liu-Type Estimator, Modified Restricted Liu-Type Estimator, Logistic Regression Model
Kaynak
Communications In Statistics-Theory And Methods
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
49
Sayı
9
