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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/20724


    Title: Optimal step-stress test under type I progressive group-censoring with random removals
    Authors: Wu, Shuo-jye;Lin, Ying-po;Chen, Shyi-tien
    Contributors: 淡江大學統計學系
    Keywords: A-optimality;D-optimality;E-optimality;Grouped data;Maximum likelihood method;Progressive type I censoring;Variance-optimality
    Date: 2008-04
    Issue Date: 2010-08-10 10:27:56 (UTC+8)
    Publisher: Elsevier
    Abstract: Some traditional life tests result in no or very few failures by the end of test. In such cases, one approach is to do life testing at higher-than-usual stress conditions in order to obtain failures quickly. This paper discusses a k-level step-stress accelerated life test under type I progressive group-censoring with random removals. An exponential failure time distribution with mean life that is a log-linear function of stress and a cumulative exposure model are considered. We derive the maximum likelihood estimators of the model parameters and establish the asymptotic properties of the estimators. We investigate four selection criteria which enable us to obtain the optimum test plans. One is to minimize the asymptotic variance of the maximum likelihood estimator of the logarithm of the mean lifetime at use-condition, and the other three criteria are to maximize the determinant, trace and the smallest eigenvalue of Fisher's information matrix. Some numerical studies are discussed to illustrate the proposed criteria.
    Relation: Journal of Statistical Planning and Inference 138(4), pp.817-826
    DOI: 10.1016/j.jspi.2007.02.004
    Appears in Collections:[統計學系暨研究所] 期刊論文

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