Abstract
In this paper we provide a hands-on discussion of the use of the HyperStar phase-type fitting tool in common application scenarios. HyperStar allows fitting Hyper-Erlang distributions to empirical data, using a variety of algorithms and operation modes. We describe simple cluster-based fitting, a new graphical method for refining the density approximation, a new command-line interface, and the integration of HyperStar with a Mathematica implementation of a fitting algorithm. Furthermore, we describe the use of Hyper-Erlang distributions in simulation. Throughout our discussion we illustrate the concepts on a data set which has been shown to be difficult to fit with a PH distribution.
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Reinecke, P., Krauß, T., Wolter, K. (2013). Phase-Type Fitting Using HyperStar. In: Balsamo, M.S., Knottenbelt, W.J., Marin, A. (eds) Computer Performance Engineering. EPEW 2013. Lecture Notes in Computer Science, vol 8168. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40725-3_13
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DOI: https://doi.org/10.1007/978-3-642-40725-3_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40724-6
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