Estimation of a Simple Queuing System WithUnits-in-Service and Complete Data
AbstractQueuing theory may be useful for analyzing economic phenomena involving count and duration data. We develop maximum likelihood estimators for the time-varying parameters of a simple queuing system based on two kinds of data: complete interarrival and service times (IST), and number of units in service (NIS). The IST estimator dominates the NIS estimator, in terms of ease of implementation, bias, and variance. The model is useful for many empirical applications in economics.
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Bibliographic InfoPaper provided by University of California, Davis, Department of Economics in its series Working Papers with number 535.
Date of creation: 04 Nov 2005
Date of revision:
m (t)/M (t)/8 queue; infinite server queue; time-varying parameters; Poisson stochasticprocess; duration data;
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