Statistical Inference of a Chen Lifetime Competing Risks Model Based On Improved Adaptive Type-II Progressive Censored Data

Abstract

This paper studies different failure modes for endurance of insulation of electrodes under high voltage stress. A competing risks model is studied under improved adaptive type-II progressive censoring scheme (IAT-II PCS) referring to this phenomena. Two independent competing causes of failure are considered where lifetime of these failures are assumed to follow Chen distribution with unknown scale and shape parameters. Maximum likelihood estimators (MLEs) of the unknown parameters are derived. Existence and uniqueness properties of MLEs have been studied. Asymptotic confidence intervals (ACIs) are also constructed using asymptotic normality property of the MLE. Bayes estimates are obtained with respect to both non-informative priors (NIP) and informative priors (IP) under different loss functions. Highest posterior density (HPD) credible intervals are calculated. A Monte Carlo simulation study is conducted to compare the performance of the proposed estimates. Three optimality criteria are studied to obtain the optimal censoring scheme. Finally, a real-life dataset analyzed for further validation of the proposed methods.