Inference for Burr-XII Masked System Lifetime Data in Step-Stress Partially Accelerated Life Test with Type-I Progressive Hybrid Censoring

Abstract

This article considers a step-stress partially accelerated life tests for series system model where independent and non-identical Burr XII-distributed lifetimes are assumed for the components. Based on Type-I progressive hybrid censored and masked data, expectation maximum algorithm combined with auxiliary variables is developed for estimating the model parameters and the acceleration factor. In addition, the asymptotic confidence intervals are constructed by the parametric bootstrap method. Furthermore, the proposed method is illustrated through a simulation study under various masking levels.