Partial Bayes Estimation of Two Parameter Gamma Distribution Under Non-Informative Prior

In Bayesian analysis, empirical and hierarchical methods are two main approaches for the estimation of parameter(s) involved in prior distribution one parameter. But multi-parameter model, e.g., Gamma(α, p), where both parameters unknown, idea ‘Partial Bayes (PB) Estimation’ is introduced. When we do no have proper belief regarding joint variable when estimating parameter presence others, such method may be used. Partial scale p done by putting estimate another α obtained some other classical case Gamma distribution. Using non-informative computing risk, it found that estimator has less risk than estimator. For this, simulation studies choices shape values been done. parameter, posterior mean variance evaluated through simulations to obtain with known Finally after fifitting this distribution, real datasets illustrated see performance