Model Fitting for Homogeneous BMAPs

Lothar Breuer
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Lothar Breuer: University of Trier, Department of Computer Science

Chapter Chapter 6 in From Markov Jump Processes to Spatial Queues, 2003, pp 75-88 from Springer

Abstract: 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.

Keywords: Interarrival Time; Observe Time Series; Batch Arrival; MARKOV Jump Process; Arrival Stream (search for similar items in EconPapers)
Date: 2003
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DOI: 10.1007/978-94-010-0239-4_6

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