A distribution for the service model
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
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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Repositório Institucional da UNESP |
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2946 |
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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 |
|
_version_ |
1808129401462718464 |