| dc.description.abstract | This study develops credibility predictors of aggregate losses using NHIF data of
the number of patients with same ailments in two different hospitals. For a model of
aggregate losses, the interest is in predicting both the claim number process as well as the
claim amount process. We consider a cross-section of risk classes with NHIF claims
available for each risk class, this will help to explain and predict both the claim number
and claim amount process.
For marginal claims distributions this study uses generalized linear models, an
extension of linear regression to describe cross-sectional characteristics. Copulas
function is used to model the dependencies from the joint distribution functions and so
separate out the dependence structure from the marginal distribution functions. The
claim number process is represented using a poison regression model that is conditioned
on sequence of variables, these variables drive the serial dependencies amount claims
numbers, their joint distribution is represented using copula. | en |
