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Publication details
Multiple change point detection by sparse parameter estimation
Authors | |
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Year of publication | 2010 |
Type | Article in Proceedings |
Conference | Proceedings of COMPSTAT'2010, 19th International Conference on Computational Statistics |
MU Faculty or unit | |
Citation | |
Web | http://www.econ.muni.cz/~vesely/papers/Compstat10.pdf |
Field | Applied statistics, operation research |
Keywords | multiple change point detection; overparametrized model; sparse parameter estimation; basis pursuit algorithm |
Description | The contribution is focused on multiple change point detection in a onedimensional stochastic process by sparse parameter estimation from an overparametrized model. Stochastic process with changes in the mean is estimated using dictionary consisting of Heaviside functions. The basis pursuit algorithm is used to get sparse parameter estimates. Some properties of mentioned method are studied by simulations. |
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