Inferences for Joint Hybrid Progressive Censored Exponential Lifetimes under Competing Risk Model

The aim of this paper is devoted to the problem of comparative life tests under joint censoring samples from an exponential distribution with competing risks model. This problem is considered under the consideration that only two causes of failure are occurring and the units come from two production lines such that the exponential failure time of units is censored under a hybrid progressive Type-I censoring scheme. Maximum likelihood estimation and different Bayes methods of estimation are discussed. The asymptotic confidence intervals as well as the Bayes credible intervals are established. A real data set representing time to failure on two groups of strain male mice receiving radiation is analyzed for illustrative purposes. All theoretical results are assessed and compared through the Monte Carlo study.

Automated summary

This paper addresses the problem of comparative life tests under joint censoring samples from an exponential distribution with competing risks model, focusing on two causes of failure and units from two production lines censored under a hybrid progressive Type-I censoring scheme. Maximum likelihood estimation, different Bayes methods, asymptotic confidence intervals, and Bayes credible intervals are discussed, with a real data set analyzed for illustrative purposes. Theoretical results are evaluated and compared through Monte Carlo studies.