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Kalman Filtering
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SYSNO ASEP 0347794 Document Type M - Monograph Chapter R&D Document Type Monograph Chapter Title Statistical State-Space Modeling via Kalman Filtration Author(s) Brabec, Marek (UIVT-O) RID, SAI, ORCID Source Title Kalman Filtering. - New York : Nova Science Publishers, 2011 / Gomez J.M. - ISBN 978-1-61761-462-0 Pages s. 77-110 Number of pages 34 s. Number of pages 385 Language eng - English Country US - United States Keywords kalman filter ; state-space ; time-series model ; prediction error decomposition ; statistical estimation Subject RIV BB - Applied Statistics, Operational Research CEZ AV0Z10300504 - UIVT-O (2005-2011) EID SCOPUS 84895359112 Annotation We start with a brief review of the theory underlying the Kalman filter (KF) statistical modeling based on the state-space approach. We will stress the prediction error decomposition as a highly effective way of computing the likelihood function, useful when maximum likelihood estimate of certain structural parameters is attempted. Next, we will illustrate how the state-space modeling and KF can be useful for solving practical problems from interesting real-life applications. Firstly, the state-space approach and KF estimation will be shown as a tool for estimation of time-varying parameters describing radon concentrations in houses, based on two underlying differential equations summarizing the radon and tracer dynamics. Secondly, we will show how the Kalman filtration can be useful for estimation of underlying growth curve of small children. Further, we will consider also multivariate approach useful for individualized natural gas consumption modeling. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2012 Electronic address https://www.novapublishers.com/catalog/product_info.php?products_id=28940
Number of the records: 1