Bayesian Estimation Based on Sequential Order Statistics for Heterogeneous Baseline Gompertz Distributions

A composite dynamic system (CDS) is composed of multiple components. Each component failure can equally induce higher loading on the surviving components and, hence, enhances hazard rate each component. The applications CDS and reliability evaluation has earned more attention in recent two decades. Because lifetime quality could be inconsistent, lifetimes considered to follow heterogeneous baseline Gompertz distributions this study. power-trend function used order characterize CDS. In overcome difficulty obtaining reliable estimates parameters model, Bayesian estimation method utilizing a hybrid Gibbs sampling Metropolis-Hasting algorithm implement Markov chain Monte Carlo approach proposed for Bayes estimators parameters. An intensive simulation study carried out evaluate performance method. results show that providing information example regarding service small electric carts illustration.