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Lookup NU author(s): Dr Katinka Wolter
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We present a clustering-based fitting approach for phase-type distributions that is particularly suited to capture common characteristics of empirical data sets. The distributions fitted by this approach are especially useful in efficient simulation approaches. We describe the Hyper-* tool, which implements the algorithm and offers a user-friendly interface to efficient phase-type fitting. We provide a comparison of cluster-based fitting with segmentation-based approaches and other algorithms and show that clustering provides good results for typical empirical data sets.
Author(s): Reinecke P, Krauss T, Wolter K
Publication type: Article
Publication status: Published
Journal: Computers & Mathematics with Application
Print publication date: 10/04/2012
ISSN (print): 0898-1221
ISSN (electronic): 1873-7668
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