Help needed to tackle multicollinearity problem in count data with the help of R
Dear Umesh Khatri, The vif() function in the car package will compute (generalized) variance inflation factors for GLMs. What (if anything) to do about collinearity isn't in my opinion an answerable question without knowing the details of your research. In particular, ridge regression is not a panacea for collinearity problems. Best, John ------------------------------------------------ John Fox Sen. William McMaster Prof. of Social Statistics Department of Sociology McMaster University Hamilton, Ontario, Canada http://socserv.mcmaster.ca/jfox/ On Wed, 11 Jul 2012 19:54:48 +0530
umesh khatri <khatriumesh88 at gmail.com> wrote:
Dear everyone, I'm student of Masters in Statistics (Actuarial) from Central University of Rajasthan, India. I am doing a major project work as a part of the degree. My major project deals with fitting a glm model for the data of car insurance. I'm facing the problem of multicollinearity for this data which is visible by the plotting of data. But I'm not able to test it. In the case of linear models one can use VIF but what about count data. Another problem is as the multicollinearity is visible from the plot one solution is poisson ridge regression. But how to do the programming for this in R. I thought of making changes to "glm.fit" might help. But the codes are beyond my understanding. I'll be glad if someone can help me in this regard. -- Regards Umesh Khatri
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