Multiple change point detection by sparse parameter estimation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14560%2F10%3A00044827" target="_blank" >RIV/00216224:14560/10:00044827 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Multiple change point detection by sparse parameter estimation
Original language 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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of COMPSTAT'2010, 19th International Conference on Computational Statistics
ISBN
978-3-7908-2603-6
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
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Publisher name
Y. Lechevallier, G. Saporta (Eds.), Physica-Verlag, a Springer Company
Place of publication
Paris (France)
Event location
Aug. 22-27, 2010, Paris-France
Event date
Jan 1, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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