Parameter estimates of general failure rate model: A Bayesian approach

Abstract

The failure rate function plays an important role in studying the lifetime distributions in reliability theory and life testing models. A study of the general failure rate model r ( t ) = a + b t θ − 1 , under squared error loss function, taking a and b independent exponential random variables, has been performed in the literature. In this article, we consider a and b not necessarily independent. The estimates of the parameters a and b under squared error loss, linex loss and entropy loss functions are obtained, and further examined using simulated and real data sets. • A general failure rate model r ( t ) = a + b t θ − 1 has been studied when a and b are not necessarily independent. • Bayes’ estimators of the parameters a and b, under symmetric and asymmetric loss functions, have been obtained. • The monotonicity of the estimators has been studied through simulated as well as real data sets