OPTIMUM CONSTANT STRESS ACCELERATED LIFE TESTS FOR THE GENERALIZED LOGISTIC DISTRIBUTION WITH PROGRESSIVE CENSORING
DOI:
https://doi.org/10.59743/jbs.v27i.84Keywords:
Accelerated Life Test, Constant stress, Maximum Likelihood, Progressive Censoring, Generalized Logistic Distribution, Inverse Power Law Function, Test PlanAbstract
This paper deals with non-Bayesian analysis of constant stress Accelerated Life Test (ALT) when the lifetime of the items follow Generalized Logistic Distribution (GLD). The Maximum Likelihood (ML) method of the parame- ter estimation and optimal design for Constant Stress Accelerated Life Test (CSALT) under progressive type-I grouped censoring data is contained. It is assumed that the scale parameter be an inverse power law function of the constant stress level. In addition, Fisher information matrix of the estimators are given. Finally, numerical studies are discussed to illustrate the proposed procedure.
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