Choosing the Link Function and Accounting for Link Uncertainty in Generalized Linear Models using Bayes Factors
TECHNISCHE UNIV MUNICH (GERMANY F R) MATHEMATISCHES INST
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One important component of model selection using generalized linear models GLM is the choice of a link function. Approximate Bayes factors are used to assess the improvement in fit over a GLM with canonical link when a parametric link family is used. For this approximate Bayes factors are calculated using the approximations given in Raftery 1996, together with a reference set of prior distributions. This methodology can also be used to differentiate between different parametric link families, as well as allowing one to jointly select the link family and the independent variables. This involves comparing non nested models. This is illustrated using parametric link families studied in Czado 1997 for two data sets involving binomial responses.
- Statistics and Probability