Parameter and reliability estimation of inverted Maxwell mixture model

In present study the probability density function of mixture is derived for inverse Maxwell density. The main distributional properties and reliability characteristics are studied. Maximum likelihood estimation of the pertinent parameters along with failure rate functions and reliability are obtained. The Bayesian study of anonymous parameters of inverse Maxwell mixture model, assuming three priors is considered employed distinct loss functions. The prior reliance of mixture density is characterized by the inverted gamma, uniform and Jeffreys prior. The efficiencies of the considered set of estimates of mixture distribution parameters are studied through simulation. To scrutinize the response of prior reliance and loss functions posterior risks of the Bayes estimators are figured out and differentiated. Bayes estimator assuming the informative have been observed performing better.