Bayesian inference of traffic intensity in M/M/1 queue under symmetric and asymmetric loss functions

Kushvaha Bhaskar (), Das Dhruba () and Tamuli Asmita ()
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Kushvaha Bhaskar: Department of Statistics, Dibrugarh University, Dibrugarh, India
Das Dhruba: Department of Statistics, Dibrugarh University, Dibrugarh, India
Tamuli Asmita: Department of Statistics, Dibrugarh University, Dibrugarh, India

Monte Carlo Methods and Applications, 2025, vol. 31, issue 2, 109-118

Abstract: In this article, Bayesian estimators of the traffic intensity (ρ) in single server Markovian ( M / M / 1 {M/M/1} ) queueing system are derived under the squared error loss function (SELF) and precautionary loss function (PLF). These Bayes estimators are derived using three different priors viz. beta, independent gamma and Jeffrey distribution. The effectiveness of the proposed Bayes estimators are compared in terms of their posterior risks. A suitable prior is chosen for Bayesian analysis using the model comparison criterion based on the Bayes factor.

Keywords: traffic intensity; Bayesian estimation; squared error loss function; precautionary loss function (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1515/mcma-2025-2005

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