A distribution for the service model

Detalhes bibliográficos
Autor(a) principal: Prado, Silvia Maria
Data de Publicação: 2015
Outros Autores: Louzada, Francisco, Rinaldi, José Gilberto S. [UNESP], Benze, Benedito Galvão
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1590/0101-7438.2015.035.03.0555
http://hdl.handle.net/11449/168350
Resumo: In this paper, we propose a distribution that describes a specific system. The system has a heavy traffic, a fast service and the service rate depends on state of the system. This distribution we call the Maximum-Conway-Maxwell-Poisson-exponential distribution, denoted by MAXCOMPE distribution. The MAXCOMPE distribution is obtained by compound distributions in which we use the zero truncated Conway-Maxwell-Poisson distribution and the exponential distribution. This distribution has adjustment mechanism in order to re-establish the equilibrium of the system when the traffic flow increases and that is described by variations of the pressure parameter. Because of this, the MAXCOMPE distribution contains sub-models, such as, the Maximum-geometric-exponential distribution, the Maximum-Poisson-exponential distribution and the Maximum-Bernoulli-exponential 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 shown to illustrate the applicability of the model.
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spelling A distribution for the service modelMAXCOMPE distributionServerService rateIn this paper, we propose a distribution that describes a specific system. The system has a heavy traffic, a fast service and the service rate depends on state of the system. This distribution we call the Maximum-Conway-Maxwell-Poisson-exponential distribution, denoted by MAXCOMPE distribution. The MAXCOMPE distribution is obtained by compound distributions in which we use the zero truncated Conway-Maxwell-Poisson distribution and the exponential distribution. This distribution has adjustment mechanism in order to re-establish the equilibrium of the system when the traffic flow increases and that is described by variations of the pressure parameter. Because of this, the MAXCOMPE distribution contains sub-models, such as, the Maximum-geometric-exponential distribution, the Maximum-Poisson-exponential distribution and the Maximum-Bernoulli-exponential 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 shown to illustrate the applicability of the model.Universidade Federal de Mato GrossoUniversidade de São PauloUniversidade Estadual Paulista – FCT/UNESPUniversidade Federal de São CarlosUniversidade Estadual Paulista – FCT/UNESPUniversidade Federal de Mato GrossoUniversidade de São Paulo (USP)Universidade Estadual Paulista (Unesp)Universidade Federal de São Carlos (UFSCar)Prado, Silvia MariaLouzada, FranciscoRinaldi, José Gilberto S. [UNESP]Benze, Benedito Galvão2018-12-11T16:40:54Z2018-12-11T16:40:54Z2015-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article555-576application/pdfhttp://dx.doi.org/10.1590/0101-7438.2015.035.03.0555Pesquisa Operacional, v. 35, n. 3, p. 555-576, 2015.1678-51420101-7438http://hdl.handle.net/11449/16835010.1590/0101-7438.2015.035.03.0555S0101-743820150003005552-s2.0-84956871009S0101-74382015000300555.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPesquisa Operacional0,365info:eu-repo/semantics/openAccess2024-01-05T06:24:52Zoai:repositorio.unesp.br:11449/168350Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:11:03.438388Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A distribution for the service model
title A distribution for the service model
spellingShingle A distribution for the service model
Prado, Silvia Maria
MAXCOMPE distribution
Server
Service rate
title_short A distribution for the service model
title_full A distribution for the service model
title_fullStr A distribution for the service model
title_full_unstemmed A distribution for the service model
title_sort A distribution for the service model
author Prado, Silvia Maria
author_facet Prado, Silvia Maria
Louzada, Francisco
Rinaldi, José Gilberto S. [UNESP]
Benze, Benedito Galvão
author_role author
author2 Louzada, Francisco
Rinaldi, José Gilberto S. [UNESP]
Benze, Benedito Galvão
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Federal de Mato Grosso
Universidade de São Paulo (USP)
Universidade Estadual Paulista (Unesp)
Universidade Federal de São Carlos (UFSCar)
dc.contributor.author.fl_str_mv Prado, Silvia Maria
Louzada, Francisco
Rinaldi, José Gilberto S. [UNESP]
Benze, Benedito Galvão
dc.subject.por.fl_str_mv MAXCOMPE distribution
Server
Service rate
topic MAXCOMPE distribution
Server
Service rate
description In this paper, we propose a distribution that describes a specific system. The system has a heavy traffic, a fast service and the service rate depends on state of the system. This distribution we call the Maximum-Conway-Maxwell-Poisson-exponential distribution, denoted by MAXCOMPE distribution. The MAXCOMPE distribution is obtained by compound distributions in which we use the zero truncated Conway-Maxwell-Poisson distribution and the exponential distribution. This distribution has adjustment mechanism in order to re-establish the equilibrium of the system when the traffic flow increases and that is described by variations of the pressure parameter. Because of this, the MAXCOMPE distribution contains sub-models, such as, the Maximum-geometric-exponential distribution, the Maximum-Poisson-exponential distribution and the Maximum-Bernoulli-exponential 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 shown to illustrate the applicability of the model.
publishDate 2015
dc.date.none.fl_str_mv 2015-09-01
2018-12-11T16:40:54Z
2018-12-11T16:40:54Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1590/0101-7438.2015.035.03.0555
Pesquisa Operacional, v. 35, n. 3, p. 555-576, 2015.
1678-5142
0101-7438
http://hdl.handle.net/11449/168350
10.1590/0101-7438.2015.035.03.0555
S0101-74382015000300555
2-s2.0-84956871009
S0101-74382015000300555.pdf
url http://dx.doi.org/10.1590/0101-7438.2015.035.03.0555
http://hdl.handle.net/11449/168350
identifier_str_mv Pesquisa Operacional, v. 35, n. 3, p. 555-576, 2015.
1678-5142
0101-7438
10.1590/0101-7438.2015.035.03.0555
S0101-74382015000300555
2-s2.0-84956871009
S0101-74382015000300555.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Pesquisa Operacional
0,365
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 555-576
application/pdf
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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