Constant- Stress Partially Accelerated Life Tests on Masked Series Systems under Progressive Type II Censoring

Abstract

In this paper, we discuss the parametric estimation of the constant-stress partially accelerated life test on masked series system, where complementary exponential distributed lifetimes are assumed for the components. Based on the progressive type II censored and masked system life data, the maximum-likelihood estimates (MLEs) of the unknown parameters and acceleration factor are derived. Also, the Bayesian estimates (BEs) of the unknown parameters and the acceleration factor are obtained by using Gibbs sample algorithm and adaptive rejection sampling method under independent symmetrical triangular priors and Gamma prior respectively. The effectiveness of MLEs and BEs are compared through the Monte Carlo simulation under different masking levels and censoring schemes.