analysis of diabetes using copula generalized additive regression model

Copulas are important tools to construct multivariate distributions using their marginals. these functions provide a flexible way to measure the strength of dependency structure among variables. in many cases, the parameters of the marginals and copula are a response related to a set of covariates. considering the covariates affect in the accuracy of copula parameters estimation. generalized additive model (gam) is a flexible models which capture a linear and non-linear relationships between response and explanatory variables. in this paper application of gam model in copula is investigated. next, using copula gam the best model is determined for analyzing diabetic patients in ilam province.