PEMODELAN COPULA CLAYTON UNTUK PREDIKSI KLAIM PADA DATA LONGITUDINAL DENGAN EXCESS ZEROS
Abstract
This papper discuss about longitudinal data models of claim counts with
excess-zeros, in which time-dependence of the claim counts is modeled by using a
copula function. The copula approach extensively to model the serial dependence of
the claim counts in car insurance, to model this serial dependence of the claim
counts (between the history and future claims). The maximum likelihood is applied
to estimate the parameters of the discrete copula model. A two-step procedure is
proposed to estimate the parameters and predict the claim counts of the next period
using the estimated parameters.
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