Influence diagnostics in gamma ridge regression model

ABSTRACT

In this article, we proposed some influence diagnostics for the gamma regression model (GRM) and the gamma ridge regression model (GRRM). We assess the impact of influential observations on the GRM and GRRM estimates by extending the work of Pregibon [Logistic regression diagnostics. Ann Stat. 1981;9:705–724] and Walker and Birch [Influence measures in ridge regression. Technometrics. 1988;30:221–227]. Comparison of both models is made and demonstrated with the help of a simulation study and a real data set. We report some momentous results in detecting the influential observations and their effects on the GRM and GRRM estimates.

KEYWORDS:

• GRM
• GRRM
• influential observation
• Pearson residuals
• multicollinearity
• ridge estimates

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Muhammad Amin http://orcid.org/0000-0002-7431-5756

Muhammad Aslam http://orcid.org/0000-0003-2290-2307