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Model Fitting for Homogeneous BMAPs

In: From Markov Jump Processes to Spatial Queues

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  • Lothar Breuer

    (University of Trier, Department of Computer Science)

Abstract

Although the concept of BMAPs has gained widespread use in stochastic modelling of communication systems and other application areas, there are few statistical methods of parameter estimation proposed yet. A survey of estimation methods is given in Asmussen [4]. His emphasis is on maximum likelihood estimation and its implementation via the EM algorithm. For the Markov Modulated Poisson Process (MMPP), an EM algorithm has been developed by Ryden [114, 115, 116, 117], whereas Asmussen et al. [7] derived a fitting procedure for phase-type distributions via the EM algorithm. An in?teresting different approach is given by Botta et al. [20] and Chauveau et al. [37]. They introduce the class of generalized hyperexponential distributions and derive statistical fitting methods by means of inversion of transforms.

Suggested Citation

  • Lothar Breuer, 2003. "Model Fitting for Homogeneous BMAPs," Springer Books, in: From Markov Jump Processes to Spatial Queues, chapter 0, pages 75-88, Springer.
    • Handle: RePEc:spr:sprchp:978-94-010-0239-4_6
    DOI: 10.1007/978-94-010-0239-4_6
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