Liu estimator in logistic regression when the data are collinear
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Tarih
2008
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Vilnius Gediminas Technical Univ Press, Technika
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The logistic regression model is used to predict a binary response variable. Logistic regression using maximum likelihood estimation has gained widespread use but it is found that multicollinearity among the independent variables inflates the variance of this estimator. Previously, Ridge, Principal Component and Stein estimators were proposed instead of maximum likelihood estimator when the data are collinear. And in this study a Liu type estimator is proposed that will have smaller mean squared error than the maximum likelihood estimator. And Liu type estimator and several alternative estimators in logistic regression, such as Ridge, Stein, principal component, are compared under the mean squared error criterion.
Açıklama
20th International Conference/Euro Mini Conference on Continuous Optimization and Knowledge-Based Technologies (EurOPT 2008) -- MAY 20-23, 2008 -- Neringa, LITHUANIA
Anahtar Kelimeler
Logistic Regression, Collinearity, Maximum Likelihood Estimator (Mle), Ridge Logistic, Estimator, Stein Estimator, Liu Estimator
Kaynak
20th International Conference, Euro Mini Conference Continuous Optimization and Knowledge-Based Technologies, Europt'2008
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
