Impact of Serial Correlation on  Change Point Detection by Sparse Parameter Estimation

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Authors	NEUBAUER Jiří VESELÝ Vítězslav
Year of publication	2011
Type	Article in Proceedings
Conference	10th International Conference APLIMAT 2011
MU Faculty or unit	Faculty of Economics and Administration
Citation
Web	http://archiv.aplimat.com/2011/Proceedings/Modeling_and_Simulation/Neubauer_Vesely.pdf
Field	Applied statistics, operation research
Keywords	change point detection; overparametrized model; sparse parameter estimation; serial correlation
Description	The contribution deals with change point detection in a one-dimensional stochastic process when using sparse parameter estimation from an overparametrized model. A stochastic process with change in the mean is estimated using dictionary consisting of Heaviside functions. The basis pursuit algorithm is applied to get sparse parameter estimates. Impact of serial correlations on change point detection is studied by simulations.
Related projects:	Dynamic Geovisualisation in Crises Management