Modified ridge-type estimator for the gamma regression model. Issue 9 (27th September 2022)

• Record Type: Journal Article
• Authors: Lukman, Adewale F.; Ayinde, Kayode; Kibria, B. M. Golam; Adewuyi, Emmanuel T.
• Is Part Of: Communications in statistics. Volume 51:Issue 9(2022)
• Page Start: 5009
• Page End: 5023
• Publication Date: 2022-09-27
• Subjects: Gamma modified ridge-type -- Gamma regression -- Linear regression model -- Modified ridge-type; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2020.1752720
• Languages: English
• ISSNs: 0361-0918

Abstract

Abstract: 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.