dc.contributorUniversidade Federal de Mato Grosso do Sul (UFMS)
dc.contributorUniversidade de São Paulo (USP)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorUniversidade Federal de São Carlos (UFSCar)
dc.date.accessioned2018-11-26T15:28:15Z
dc.date.available2018-11-26T15:28:15Z
dc.date.created2018-11-26T15:28:15Z
dc.date.issued2015-01-01
dc.identifierAdvances And Applications In Statistics. Allahabad: Pushpa Publishing House, v. 44, n. 1, p. 1-19, 2015.
dc.identifier0972-3617
dc.identifierhttp://hdl.handle.net/11449/158594
dc.identifierWOS:000365188200001
dc.description.abstractIn this paper, we show a distribution that describes a specific system. The system has a single server, a heavy traffic and a fast service. In addition, there is an adjustment mechanism when the number of customers increases. This distribution we call the Maximum-Conway-Maxwell-Poisson-Weibull distribution, denoted by MAXCOMPW distribution. The MAXCOMPW distribution is obtained by compound distributions in which we use the zero truncated Conway-Maxwell-Poisson distribution and the Weibull distribution. The MAXCOMPW distribution contains sub-models that describe the variations of the system, such as, Maximum-geometric-Weibull distribution, Maximum-Poisson-Weibull distribution and Maximum-Bernoulli-Weibull distribution. The properties of the proposed distribution are discussed, including formal proof of its density function and explicit algebraic formulas for their reliability function and moments. The parameter estimation is based on the usual maximum likelihood method. Simulated and real data are used to illustrate the applicability of the model.
dc.languageeng
dc.publisherPushpa Publishing House
dc.relationAdvances And Applications In Statistics
dc.rightsAcesso restrito
dc.sourceWeb of Science
dc.subjectMAXCOMPW distribution
dc.subjectpressure parameter
dc.subjectservice time
dc.titleA DISTRIBUTION FOR SERVICE MODEL
dc.typeArtículos de revistas


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