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Multivariate Extensions of Univariate Life Distributions

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  • Roy, Dilip
  • Mukherjee, S. P.

Abstract

A general approach for the development of multivariate survival models, based on a set of given marginal survivals, is presented. Preservation of IFR and IFRA properties and the nature of dependence among the variables are examined, and a recursive relation is suggested to obtain the resultant density function. In particular, an absolutely continuous Weibull distribution is derived and a few of its properties are studied.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Multivariate Analysis.

Volume (Year): 67 (1998)
Issue (Month): 1 (October)
Pages: 72-79

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Handle: RePEc:eee:jmvana:v:67:y:1998:i:1:p:72-79

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Related research

Keywords: Characterization modelling marginal distribution joint distribution IFR and IFRA classes Weibull distribution exponential distribution failure rate transform crude hazard rates;

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  1. Shanbhag, D. N. & Kotz, S., 1987. "Some new approaches to multivariate probability distributions," Journal of Multivariate Analysis, Elsevier, vol. 22(2), pages 189-211, August.
  2. Shaked, Moshe, 1982. "A general theory of some positive dependence notions," Journal of Multivariate Analysis, Elsevier, vol. 12(2), pages 199-218, June.
  3. Lee, Larry, 1979. "Multivariate distributions having Weibull properties," Journal of Multivariate Analysis, Elsevier, vol. 9(2), pages 267-277, June.
  4. Elandt-Johnson, Regina C., 1978. "Some properties of bivariate Gumbel Type A distributions with proportional hazard rates," Journal of Multivariate Analysis, Elsevier, vol. 8(2), pages 244-254, June.
  5. Johnson, N. L. & Kotz, Samuel, 1975. "A vector multivariate hazard rate," Journal of Multivariate Analysis, Elsevier, vol. 5(1), pages 53-66, March.
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