Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/286209 
Title (translated): 
Bayesian estimators of Weibull distributions applied to a model of waiting lines G/G/s
Year of Publication: 
2020
Citation: 
[Journal:] Revista de Métodos Cuantitativos para la Economía y la Empresa [ISSN:] 1886-516X [Volume:] 30 [Year:] 2020 [Pages:] 142-162
Publisher: 
Universidad Pablo de Olavide, Sevilla
Abstract (Translated): 
The approximation of G/G/s models from Markov models M/M/s has been studied in the literature. The study of a queue model is detailed in the present article, using times of arrivals and time service distributed by Weibull whose estimation of parameters was performed with the Bayesian method Monte Carlo Markov chain, specifically the Gibbs sampler. The approximations of this model of waiting lines is evaluated by simulation. This methodology was applied to the case of delivery of refreshments to students of the University of Magdalena in Santa Marta, Colombia. The results show the utility and power to calculate indicators of a queue system when both, the arrival and attention times, are distributed as a Weibull.
Subjects: 
queue system
Monte Carlo Markov chain
Weibull distribution
bayesianestimation
JEL: 
C11
C13
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Article

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