Título :	Change point estimation in an M/M/2 queue with heterogeneous servers
Autor :	Singh, Saroja Kumar Acharya, Sarat Kumar Cruz, Frederico Rodrigues Borges da Cançado, André Luiz Fernandes
metadata.dc.identifier.orcid:	https://orcid.org/0000-0003-2558-1836 https://orcid.org/0000-0002-6349-5624 https://orcid.org/0000-0001-5842-5544 https://orcid.org/0000-0002-7019-8521
metadata.dc.contributor.affiliation:	Ravenshaw University, Department of Statistics Sambalpur University, Department of Statistics Universidade Federal de Minas Gerais, Departamento de Estatística Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Estatística, Programa de Pós-Graduação em Estatística
Assunto::	Estimação de máxima verossimilhança Simulação de Monte Carlo Teoria das filas
Fecha de publicación :	6-may-2023
Editorial :	Elsevier
Citación :	SINGH, Saroja Kumar; ACHARYA, Sarat Kumar; CRUZ, Frederico Rodrigues Borges da; CANÇADO, André Luiz Fernandes. Change point estimation in an M/M/2 queue with heterogeneous servers. Mathematics and Computers in Simulation, [S.l], v. 212, p. 182-194, 2023. DOI: https://doi.org/10.1016/j.matcom.2023.04.022. Disponível em: https://www.sciencedirect.com/science/article/pii/S0378475423001775?via%3Dihub. Acesso em: 02 jun. 2025.
Abstract:	The change point problem in the inter-arrival time of an M/M/2 queue with heterogeneous servers is studied here. In this model, it is assumed that the queue is in a steady state and that customers are served by the fastest available server and that there is no transfer of customers between servers. Maximum likelihood estimators are deducted for the arrival rates after and before the change point and for the service rates. Monte Carlo simulation results are presented that attest to the effectiveness and efficiency of the deduced estimators.
metadata.dc.description.unidade:	Instituto de Ciências Exatas (IE) Departamento de Estatística (IE EST)
metadata.dc.description.ppg:	Programa de Pós-Graduação em Estatística
DOI:	https://doi.org/10.1016/j.matcom.2023.04.022
metadata.dc.relation.publisherversion:	https://www.sciencedirect.com/science/article/pii/S0378475423001775?via%3Dihub
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