Modified ridge-type estimator for the gamma regression model

• Published in: Communications 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
• Language: English
• 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
• ISSN: 0361-0918; 1532-4141
• DOI: 10.1080/03610918.2020.1752720

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.