On the Estimation of Expected Proportion of AIDS Cases Using Bayesian Approach

In this paper, a new approach is proposed for estimating the proportion of HIV infected population converting to AIDS. The consideration of Bayesian method is motivated by its use as a powerful statistical tool. The method proposed by Clayton and Kaldor (1987) is followed to obtain the empirical Bayes estimates. A suitable parametric model is proposed for the prior density. The parameters of the posterior distribution are estimated using the method of maximum likelihood. The proposed methodology has also been investigated with an example