Statistical inference of Step-Stress Partially Accelerated Life Tests Using the Chen Distribution With Progressive Censoring Data Type-II

Abstract

This memory focuses on Step-Stress Partially Accelerated Life Tests (SS-PALT) applied to products with a two-parameter bathtub-shaped lifetime distribution, specifically the Chen distribution. The objective is to estimate the distribution parameters and acceleration factor using maximum likelihood estimation (MLE) based on progressive Type-II censoring. The thesis also provides the asymptotic variance and covariance matrix of the estimators. To establish confidence intervals (CIs) for the parameters, two approaches are employed: the normal approximation to the asymptotic distribution of the MLEs and the bootstrap method. The estimators are numerically obtained using the Mathematica Package through an iterative procedure. To demonstrate the proposed estimation method, a numerical example is presented. Furthermore, a realworld example is provided to illustrate the suggested approach. Keywords: Chen distribution; Step-stress partially accelerated life tests; Progressive Type-II censoring; Maximum likelihood estimation; Asymptotic confidence intervals