Article ID Journal Published Year Pages File Type
468327 Computers & Mathematics with Applications 2012 12 Pages PDF
Abstract

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.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science (General)
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