NONSTATIONARY LOSS QUEUES VIA CUMULANT MOMENT APPROXIMATIONS
2014 ◽
Vol 29
(1)
◽
pp. 27-49
◽
Keyword(s):
The Mean
◽
In this paper, we provide a new technique for analyzing the nonstationary Erlang loss queueing model with abandonment. Our method uniquely combines the use of the functional Kolmogorov forward equations with the well-known Gram-Charlier series expansion from the statistics literature. Using the Gram-Charlier series expansion, we show that we can estimate salient performance measures of the loss queue such as the mean, variance, skewness, kurtosis, and blocking probability. Lastly, we provide numerical examples to illustrate the effectiveness of our approximations.