BAYESIAN ESTIMATION OF ERLANG DISTRIBUTION UNDER DIFFERENT PRIOR DISTRIBUTIONS
This paper addresses the problem of Bayesian estimation of the parameters of Erlang distribution under squared error loss function by assuming different independent informative priors as well as joint priors for both shape and scale parameters. The motivation is to explore the most appropriate prior for Erlang distribution among different priors. A comparison of the Bayes estimates and their risks for different choices of the values of the hyperparameters is also presented. Finally, we illustrate the results using a simulation study as well as by doing real data analysis.