Compounded Inverse Weibull Distributions: Properties, Inference and Applications

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dc.contributor.author Chakrabarty, Jimut Bahan
dc.contributor.author Chowdhury, Shovan
dc.date.accessioned 2017-05-19T06:24:06Z
dc.date.available 2017-05-19T06:24:06Z
dc.date.issued 2016-12
dc.identifier.uri http://hdl.handle.net/2259/938
dc.description.abstract In this paper two probability distributions are introduced compounding inverse Weibull distribution with Poisson and geometric distributions. The distributions can be used to model lifetime of series system where the lifetimes follow inverse Weibull distribution and the subgroup size being random follows either geometric or Poisson distribution. Some of the important statistical and reliability properties of each of the distributions are derived. The distributions are found to exhibit both monotone and non-monotone failure rates. The parameters of the distributions are estimated using the maximum likelihood method and the expectation-maximization algorithm. The potentials of the distributions are explored through three real life data sets and are compared with similar compounded distributions, viz. Weibull-geometric, Weibull-Poisson, exponential-geometric and exponential-Poisson distributions. en_US
dc.language.iso en en_US
dc.publisher Indian Institute of Management en_US
dc.relation.ispartofseries ;IIMK/WPS/213/QM&OM/2016/25
dc.subject Inverse Weibull distribution en_US
dc.subject Poisson distribution en_US
dc.subject Geometric distribution en_US
dc.subject Hazard function en_US
dc.subject Maximum likelihood estimation en_US
dc.subject EM algorithm. en_US
dc.title Compounded Inverse Weibull Distributions: Properties, Inference and Applications en_US
dc.type Working Paper en_US


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  • 2016 [9]
    Working Papers Published in the year 2016

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