Abstract
Stochastic models based on matrix-exponential structures, like matrix-exponential distributions and rational arrival processes (RAPs), have gained popularity in analytical models recently. However, the application of these models in simulation-based evaluations is not as widespread yet. One of the possible reasons is the lack of efficient random-variate-generation methods. In this chapter we propose methods for efficient random-variate generation for matrix-exponential stochastic models based on appropriate representations of the models.
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Horváth, G., Telek, M. (2013). Acceptance-Rejection Methods for Generating Random Variates from Matrix Exponential Distributions and Rational Arrival Processes. In: Latouche, G., Ramaswami, V., Sethuraman, J., Sigman, K., Squillante, M., D. Yao, D. (eds) Matrix-Analytic Methods in Stochastic Models. Springer Proceedings in Mathematics & Statistics, vol 27. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4909-6_7
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