Detection of Changes in the Czech Consumer Price Index by Sparse Parameter Estimation

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Authors	NEUBAUER Jiří VESELÝ Vítězslav
Year of publication	2010
Type	Article in Periodical
Magazine / Source	Forum Statisticum Slovacum
MU Faculty or unit	Faculty of Economics and Administration
Citation
Web	http://www.ssds.sk/casopis/archiv/2010/fss0510.pdf
Field	Applied statistics, operation research
Keywords	multiple change point detection; overparametrized model; sparse parameter estimation; basis pursuit algorithm; consumer price index
Description	The contribution is focused on application of multiple change point detection in a one-dimensional stochastic process by sparse parameter estimation from an overparametrized model. A 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. The mentioned method is applied to the time series of the Czech consumer price index.
Related projects:	Dynamic Geovisualisation in Crises Management