Model-based clustering and segmentation of time series with changes in regime

25 Dec 2013Allou SaméFaicel ChamroukhiGérard GovaertPatrice Aknin

Mixture model-based clustering, usually applied to multidimensional data, has become a popular approach in many data analysis problems, both for its good statistical properties and for the simplicity of implementation of the Expectation-Maximization (EM) algorithm. Within the context of a railway application, this paper introduces a novel mixture model for dealing with time series that are subject to changes in regime... (read more)

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