6533b85efe1ef96bd12bfbaa

RESEARCH PRODUCT

Bayesian hierarchical models in manufacturing bulk service queues

Carmen ArmeroDavid Conesa

subject

Statistics and ProbabilityQueueing theoryMathematical optimizationApplied MathematicsBayesian probabilityPosterior probabilityInversion (meteorology)Markov chain Monte CarloHierarchical database modelsymbols.namesakesymbolsEconometricsStatistics Probability and UncertaintyQueueMcmc algorithmMathematics

description

In this paper, Queueing Theory and Bayesian statistical tools are used to analyze the congestion of various manufacturing bulk service queues with the same characteristics that are working independently of one another and in equilibrium. Hierarchical models are discussed in order to develop the whole inferential process for the parameters governing the system. Markov Chain Monte Carlo methods and numerical inversion of transforms are addressed to compute the posterior predictive distributions of the usual measures of performance in practice.

yearjournalcountryeditionlanguage
2006-02-01Journal of Statistical Planning and Inference
https://doi.org/10.1016/j.jspi.2004.07.007