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A generalized modified Weibull distribution for lifetime modeling

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  • Carrasco, Jalmar M.F.
  • Ortega, Edwin M.M.
  • Cordeiro, Gauss M.

Abstract

A four parameter generalization of the Weibull distribution capable of modeling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone as well as non-monotone failure rates, which are quite common in lifetime problems and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh and modified Weibull distributions, among others. We derive two infinite sum representations for its moments. The density of the order statistics is obtained. The method of maximum likelihood is used for estimating the model parameters. Also, the observed information matrix is obtained. Two applications are presented to illustrate the proposed distribution.

Suggested Citation

  • Carrasco, Jalmar M.F. & Ortega, Edwin M.M. & Cordeiro, Gauss M., 2008. "A generalized modified Weibull distribution for lifetime modeling," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 450-462, December.
    • Handle: RePEc:eee:csdana:v:53:y:2008:i:2:p:450-462
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    References listed on IDEAS

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    1. Nadarajah, Saralees, 2005. "On the moments of the modified Weibull distribution," Reliability Engineering and System Safety, Elsevier, vol. 90(1), pages 114-117.
    2. Bebbington, Mark & Lai, Chin-Diew & Zitikis, RiÄ ardas, 2007. "A flexible Weibull extension," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 719-726.
    3. Kundu, Debasis & Raqab, Mohammad Z., 2005. "Generalized Rayleigh distribution: different methods of estimations," Computational Statistics & Data Analysis, Elsevier, vol. 49(1), pages 187-200, April.
    4. Amit Choudhury, 2005. "A Simple Derivation of Moments of the Exponentiated Weibull Distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 62(1), pages 17-22, September.
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