Improved Shape Parameter Estimation in a Discrete Weibull Model

  • P. Araújo Santos
  • M. I. Fraga Alves
Part of the Studies in Theoretical and Applied Statistics book series (STAS)


A new shape parameter estimator for a discrete Weibull model is proposed. This estimator is based on an extension of the Khan et al. (IEEE Trans. Reliab. 38:348–350, 1989) method of proportions. Simulations are carried out to illustrate the improvement achieved in terms of bias and mean square error. The proposed estimator is applied on a financial dataset dealing with durations between violations in a quantitative risk management environment.


Moment Estimator Duration Dependence Empirical Cumulative Distribution Function Increase Failure Rate Approximate Maximum Likelihood 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This research was partially supported by Fundação para a Ciência e Tecnologia (FCT/PROTEC, FCT/OE and PTDC/FEDER) and Center of Statistics and Applications of University of Lisbon (CEAUL).


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Instituto Politécnico de Santarém, Departamento de Informática e Métodos QuantitativosEscola Superior de Gestão e TecnologiaSantarémPortugal
  2. 2.Faculdade de Ciências, Departamento de Estatística e Investigação OperacionalUniversidade de LisboaLisboaPortugal

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