A functional central limit theorem for PEPA

We present a functional central limit theorem which quantifi es, as a stochastic process, the difference between a PEPA model’s underlying CTMC and its fluid approxim at on. We generalise existing theory to handle the case of non-smooth rate functions, which is an i ssue particular to modelling problems in computer science. We verify the weak convergence empirical ly and suggest future avenues for deducing more analytic approximations from it.

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