HyperStarC is a tool for fitting MarkovArrival Processes (MAPs) to empirical data.
It uses a two-step approach, where the first step is clusterbased fitting of phase-type distributions and the second step is the construction of a correlation matrix.
In the first step, we use the cluster-based algorithm for Hyper-Erlang distribution fitting from HyperStar.
Based on the HyperErlang fitting result and the clusters of samples, in the second step we construct the correlation matrix.
The tool targets engineers and scientists who need distribution fitting for non-standard distributions but have little interest in the underlying theory.
Therefore the tool has a GUI that offers graphical presentation of the data, the fitted distribution and the empirical as well as theoretical autocorrelation.