Characterizations and modelling of multivariate lack of memory property

Martin Griffiths, H. V. Kulkarni

    Research output: Contribution to journalArticlepeer-review

    Abstract

    In this article we establish characterizations of multivariate lack of memory property in terms of the hazard gradient (whenever exists), the survival function and the cumulative hazard function. Based on one of these characterizations we establish a method of generating bivariate lifetime distributions possessing bivariate lack of memory property (BLMP) with specified marginals. It is observed that the marginal distributions have to satisfy certain conditions to be stated. The method generates absolutely continuous bivariate distributions as well as those containing a singular component. Bivariate exponential distributions due to Proschan and Sullo (Reliability and biometry, pp 423-440, 1974), Freund (in J Am Stat Assoc 56:971-977, 1961), Block and Basu (J Am Stat Assoc 89:1091-1097, 1974) and Marshall and Olkin (J Am Math Assoc 62:30-44, 1967) are generated as particular cases among others using the proposed method. Some other distributions generated using the method may be of practical importance. Shock models leading to bivariate distributions possessing BLMP are given. Some closure properties of a class of univariate failure rate functions that can generate distributions possessing BLMP and of the class of bivariate survival functions having BLMP are studied. © Springer-Verlag 2006.
    Original languageEnglish
    Pages (from-to)167-180
    Number of pages13
    JournalMetrika
    Volume64
    Issue number2
    Publication statusPublished - Oct 2006

    Keywords

    • Characterizations
    • Hazard gradient
    • Modelling
    • Multivariate lack of memory property
    • Shock models
    • Singular component

    Fingerprint

    Dive into the research topics of 'Characterizations and modelling of multivariate lack of memory property'. Together they form a unique fingerprint.

    Cite this