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Nonparametric estimation of the service time distribution in the M/G/∞ queue

Published online by Cambridge University Press:  11 January 2017

Alexander Goldenshluger*
Affiliation:
University of Haifa
*
* Postal address: Department of Statistics, University of Haifa, Haifa 31905, Israel. Email address: goldensh@stat.haifa.ac.il

Abstract

The subject of this paper is the problem of estimating the service time distribution of the M/G/∞ queue from incomplete data on the queue. The goal is to estimate G from observations of the queue-length process at the points of the regular grid on a fixed time interval. We propose an estimator and analyze its accuracy over a family of target service time distributions. An upper bound on the maximal risk is derived. The problem of estimating the arrival rate is considered as well.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 2017 

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References

Beneš, V. E. (1957). Fluctuations of telephone traffic. Bell System Tech. J. 36, 965973.Google Scholar
Bingham, N. H. and Dunham, B. (1997). Estimating diffusion coefficients from count data: Einstein–Smoluchowski theory revisited. Ann. Inst. Statist. Math. 49, 667679.Google Scholar
Bingham, N. H. and Pitts, S. M. (1999). Non-parametric estimation for the M/G/∞ queue. Ann. Inst. Statist. Math. 51, 7197.Google Scholar
Blanghaps, N., Nov, Y. and Weiss, G. (2013). Sojourn time estimation in an M/G/∞ queue with partial information. J. Appl. Prob. 50, 10441056.Google Scholar
Borovkov, A. A. (1967). Limit laws for queueing processes in multichannel systems. Siberian Math. J. 8, 746763.Google Scholar
Brillinger, D. R. (1974). Cross-spectral analysis of processes with stationary increments including the stationary G/G/∞ queue. Ann. Prob. 2, 815827.Google Scholar
Brockwell, P. J. and Davis, R. A. (1991). Time Series: Theory and Methods, 2nd edn. Springer, New York.CrossRefGoogle Scholar
Brown, M. (1970). An M/G/∞ estimation problem. Ann. Math. Statist. 41, 651654.CrossRefGoogle Scholar
Goldenshluger, A. (2015). Nonparametric estimation of service time distribution in the M/G/∞ queue and related estimation problems. Preprint. Available at https://arxiv.org/abs/1508.00076.Google Scholar
Goldenshluger, A. and Nemirovski, A. (1997). On spatially adaptive estimation of nonparametric regression. Math. Meth. Statist. 6, 135170.Google Scholar
Grübel, R. and Wegener, H. (2011). Matchmaking and testing for exponentiality in the M/G/∞ queue. J. Appl. Prob. 48, 131144.Google Scholar
Hall, P. and Park, J. (2004). Nonparametric inference about service time distribution from indirect measurements. J. R. Statist. Soc. B 66, 861875.Google Scholar
Iglehart, D. L. (1973). Weak convergence in queueing theory. Adv. Appl. Prob. 5, 570594.CrossRefGoogle Scholar
Kingman, J. F. C. (1993). Poisson Processes. Oxford University Press.Google Scholar
Lindley, D. V. (1956). The estimation of velocity distributions from counts. In Proceedings of the International Congress of Mathematicians (Amsterdam, 1954), Vol III, Noordhoff, Groningen, pp.427444.Google Scholar
Milne, R. K. (1970). Identifiability for random translations of Poisson processes. Z. Wahrscheinlichkeitsth. 15, 195201.Google Scholar
Moulines, E., Roueff, F., Souloumiac, A. and Trigano, T. (2007). Nonparametric inference of photon energy distribution from indirect measurement. Bernoulli 13, 365588.Google Scholar
Nemirovski, A. (2000). Topics in non-parametric statistics. In Lectures on Probability Theory and Statistics (Saint-Flour, 1998; Lecture Notes Math.1738), Springer, Berlin, pp.85277.Google Scholar
Parzen, E. (1962). Stochastic Processes. Holden-Day, San Francisco, CA.Google Scholar
Pickands, J., III and Stine, R. A. (1997). Estimation for an M/G/∞ queue with incomplete information. Biometrika 84, 295308.CrossRefGoogle Scholar
Reynolds, J. F. (1975). The covariance structure of queues and related processes—a survey of recent work. Adv. Appl. Prob. 7, 383415.Google Scholar
Ross, S. M. (1970). Applied Probability Models with Optimization Applications. Holden-Day, San Francisco, CA>.Google Scholar
Schweer, S. and Wichelhaus, C. (2015). Nonparametric estimation of the service time distribution in the discrete-time GI/G/∞ queue with partial information. Stoch. Process. Appl. 125, 233253.CrossRefGoogle Scholar
Tsybakov, A. B. (2009). Introduction to Nonparametric Estimation. Springer, New York.Google Scholar
Whitt, W. (1985). The renewal-process stationary-excess operator. J. Appl. Prob. 22, 156167.CrossRefGoogle Scholar
Whitt, W. (1974). Heavy traffic limit theorems for queues: a survey. In Mathematical Methods in Queueing Theory (Proc. Conf., Western Michigan Univ., Kalamazoo, MI, 1973; Lecture Notes Econom. Math. Systems98), Springer, Berlin, pp.307350.Google Scholar