Abstract
This paper provides a mathematical framework for estimation of the service time distribution and expected service time of an infinite-server queueing system with a nonhomogeneous Poisson arrival process in the case of partial information, where only the numbers of busy servers are observed over time. The problem is reduced to a statistical deconvolution problem, which is solved by using Laplace transform techniques and kernels for regularization. Upper bounds on the mean squared error of the proposed estimators are derived. Some concrete simulation experiments are performed to illustrate how the method can be applied and provide some insight in the practical performance.
Original language | English |
---|---|
Pages (from-to) | 183-207 |
Number of pages | 25 |
Journal | Stochastic Systems |
Volume | 9 |
Issue number | 3 |
DOIs | |
State | Published - Sep 2019 |
Bibliographical note
Publisher Copyright:© 2019 The Author(s).
Keywords
- M /G/∞ queue
- deconvolution
- minimax risk
- nonparametric estimation
- rate of convergence
- upper bound
ASJC Scopus subject areas
- Statistics and Probability
- Modeling and Simulation
- Statistics, Probability and Uncertainty
- Management Science and Operations Research