Abstract
Abstract For highly reliable products, a progressive stress accelerated life test has been proposed to obtain timely information of the product's lifetime distribution. This article considers a progressive stress partially accelerated life test model when the lifetime of a product under use condition follows Weibull distribution. It is assumed that the progressive stress is directly proportional to time. The statistical properties of the maximum likelihood (ML) estimators of the model parameters such as existence, uniqueness, and invariance are studied. The biases and mean square errors of the maximum likelihood estimators are computed to assess their performances in the presence of the stress method developed in this article through a Monte Carlo simulation study.
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