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Mathematics and Computers in Simulation
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Exponentiated Weibull–Poisson distribution: Model, properties and applications

Exponentiated Weibull-Poisson distribution: model, properties and applications
Authors: Eisa Mahmoudi; Afsaneh Sepahdar;

Exponentiated Weibull–Poisson distribution: Model, properties and applications

Abstract

In this paper we propose a new four-parameters distribution with increasing, decreasing, bathtub-shaped and unimodal failure rate, called as the exponentiated Weibull-Poisson (EWP) distribution. The new distribution arises on a latent complementary risk problem base and is obtained by compounding exponentiated Weibull (EW) and Poisson distributions. This distribution contains several lifetime sub-models such as: generalized exponential-Poisson (GEP), complementary Weibull-Poisson (CWP), complementary exponential-Poisson (CEP), exponentiated Rayleigh-Poisson (ERP) and Rayleigh-Poisson (RP) distributions. We obtain several properties of the new distribution such as its probability density function, its reliability and failure rate functions, quantiles and moments. The maximum likelihood estimation procedure via a EM-algorithm is presented in this paper. Sub-models of the EWP distribution are studied in details. In the end, Applications to two real data sets are given to show the flexibility and potentiality of the new distribution.

arXiv admin note: text overlap with arXiv:1206.4008

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Keywords

FOS: Computer and information sciences, EM-algorithm, Point estimation, maximum likelihood estimation, Applications of statistics, Methodology (stat.ME), residual life function, exponentiated Weibull distribution, Probability distributions: general theory, probability weighted moments, Statistics - Methodology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
36
Top 10%
Top 10%
Top 10%
Green
bronze