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.
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