Reliability analysis under constant-stress partially accelerated life tests using hybrid censored data from Weibull distribution

Abstract

This article discusses the estimation of Weibull distribution parameters based on hybrid censored data under constant-stress partially accelerated test model. Two estimation methods; maximum likelihood (ML) and percentile bootstrap (PB) are used to make statistical inference on the Weibull distribution parameters and the acceleration factor. The mean square errors of the estimators are calculated to evaluate their performances through a Monte Carlo simulation study. Moreover, the confidence intervals lengths (CILs) and their associated coverage probabilities (CPs) are obtained. Finally, to demonstrate the proposed methodology, an arithmetic example is given.

Optimal Variable Acceptance Sampling Plan under Progressive Type-II Censoring for Mixture Distribution: Applications in Breast Cancer Data

“…Also, the MLEs of the parameters and the accelerating factor. On a related note, Ismail (2016) investigated the estimation of Weibull distribution parameters based on hybrid censored data under constant-stress partially accelerated test model. Srivastava and Mittal (2013) proposed a sampling plan for products having truncated logistic distribution truncated at point zero under Type-I censoring under constant PALT.…”