Multi-class Markovian arrival processes and their parameter fitting
Performance Evaluation
Correlated phase-type distributed random numbers as input models for simulations
Performance Evaluation
An EM algorithm for markovian arrival processes observed at discrete times
MMB&DFT'10 Proceedings of the 15th international GI/ITG conference on Measurement, Modelling, and Evaluation of Computing Systems and Dependability and Fault Tolerance
An empirical comparison of MAP fitting algorithms
MMB&DFT'10 Proceedings of the 15th international GI/ITG conference on Measurement, Modelling, and Evaluation of Computing Systems and Dependability and Fault Tolerance
Traffic modeling with a combination of phase-type distributions and ARMA processes
Proceedings of the Winter Simulation Conference
A two-phase map fitting method with APH interarrival time distribution
Proceedings of the Winter Simulation Conference
Retrial queuing system with Markovian arrival flow and phase-type service time distribution
Computers and Industrial Engineering
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Fitting of the parameters of a Phase Type (PH) Distributionor a Markovian Arrival Process (MAP) according to some quantities of measured data streams is still a challenge. This paper presents a new approach which computes in two steps for a set of moments and joint moments for an Acyclic PH distribution that is expanded into a MAP.In contrast to other known approaches, parameters are computed to minimize the weighted squared difference between the measured moments and the moments of the resulting PH Distribution or MAP. The proposed approach is very flexible and allows one to generate a MAP of a predefined order to approximate a given set of moments and joint moments. It is shown that the approximation is often sufficiently accurate even with MAPs of a moderate size. However, we also show that the practical applicability of the approach is limited since the exact determination of higher order moments from traces requires an extremely high effort.