Modified ridge-type estimator for the gamma regression model

The modified ridge-type estimator has been shown to cushion the effects of multicollinearity in the linear regression model. Recent studies have shown the adverse effects of multicollinearity in the gamma regression model (GRM). We proposed a gamma modified ridge-type estimator to tackle this proble...

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Bibliographic Details
Published inCommunications in statistics. Simulation and computation Vol. 51; no. 9; pp. 5009 - 5023
Main Authors Lukman, Adewale F., Ayinde, Kayode, Kibria, B. M. Golam, Adewuyi, Emmanuel T.
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 27.09.2022
Taylor & Francis Ltd
Subjects
Cushions
Estimators
Gamma modified ridge-type
Gamma regression
Linear regression model
Modified ridge-type
Regression models
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Summary:The modified ridge-type estimator has been shown to cushion the effects of multicollinearity in the linear regression model. Recent studies have shown the adverse effects of multicollinearity in the gamma regression model (GRM). We proposed a gamma modified ridge-type estimator to tackle this problem. We derived the properties of this estimator and conducted a theoretical comparison with some of the existing estimators. A real-life example and simulation study show that the proposed estimator gains an advantage over other estimators in terms of the mean square error.
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ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2020.1752720