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Gamma Models in insurance
As we know in insurance sector claims follow exponential fmily distributions, so in oredr to build the claim severity models we use the GLM technique called gamma model.
I am trying to build insurance claim severity model in SAS using proc genmod with gamma distribution. i am getting very large values for 'scale deviance' and 'pearson scale deviance' (i.e value/df) in goodness of fit tests, where in for good model these values should be near to 1 .
what would be the probable reason for this and how could i get better results and is there any literature on gamma models used for claims severity modeling to cross validate the procedure.
Replies to This Discussion
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Permalink Reply by K.Kalyanaraman on
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Observe the histogram for claim severity and verify whether the model can be used. Or provide more information about mean, median and standard deviation of claim severity.
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Permalink Reply by Triveni Hiremath on
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Sir, i have checked histogram, it is showing gamma distribution gamma(2,3) shape, with the following details
mean=1972, median=900, sd=3621
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It seems that the distribution is positively skewed; seen from details given by you. Then use the data to fit a Gamma Distribution using say Method of moments or MLE. Once getting the parameters, they may give some information and the associated Chisquare goodness of fit test will ensure whether it could be statistically valid. Please write if you need further help to fit the distribution.
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Permalink Reply by Ralph Winters on
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Check the value against chi-square to see if the results are reasonable. If not, take a closer look at the residuals to see if you can pinpoint what is going on.
-Ralph Winters
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