Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845402849 ISBN 13: 9783845402840
Da: preigu, Osnabrück, Germania
EUR 43,30
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Signal Extraction for Linear State-Space Models | Including a free MATLAB Toolbox for Time Series Modeling and Decomposition | Miguel Jerez (u. a.) | Taschenbuch | 112 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783845402840 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Jul 2011, 2011
ISBN 10: 3845402849 ISBN 13: 9783845402840
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 49,00
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This monograph discusses the decomposition of a vector of time series, described by a linear state-space model, into trend, cyclical, seasonal, irregular and input-related components. The representation and signal-extraction methods employed provide unique advantages, notably the ability to decompose single or multiple time series, the lack of revisions as the sample increases or the independence of the method from specific model formulations. Besides a complete and self-contained presentation of this subject, this text emphasizes in the practical application of the methods described. To this end, each chapter includes several examples of the methods proposed and Appendix A provides a broad description of E4, a free MATLAB Toolbox for time series analysis that can be freely downloaded from ucm.es/info/icae/e4. An Appendix provides the source code and data references required to replicate all the practical examples. 112 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845402849 ISBN 13: 9783845402840
Da: moluna, Greven, Germania
EUR 41,05
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jerez MiguelTeaches Econometrics at Universidad Complutense de Madrid. He is engaged with his colleagues Jose Casals and Sonia Sotoca in a long-term project to apply state-space methods to standard econometric problems. An output of .
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Jul 2011, 2011
ISBN 10: 3845402849 ISBN 13: 9783845402840
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 49,00
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This monograph discusses the decomposition of a vector of time series, described by a linear state-space model, into trend, cyclical, seasonal, irregular and input-related components. The representation and signal-extraction methods employed provide unique advantages, notably the ability to decompose single or multiple time series, the lack of revisions as the sample increases or the independence of the method from specific model formulations. Besides a complete and self-contained presentation of this subject, this text emphasizes in the practical application of the methods described. To this end, each chapter includes several examples of the methods proposed and Appendix A provides a broad description of E4, a free MATLAB Toolbox for time series analysis that can be freely downloaded from ucm.es/info/icae/e4. An Appendix provides the source code and data references required to replicate all the practical examples.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 112 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845402849 ISBN 13: 9783845402840
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 49,00
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This monograph discusses the decomposition of a vector of time series, described by a linear state-space model, into trend, cyclical, seasonal, irregular and input-related components. The representation and signal-extraction methods employed provide unique advantages, notably the ability to decompose single or multiple time series, the lack of revisions as the sample increases or the independence of the method from specific model formulations. Besides a complete and self-contained presentation of this subject, this text emphasizes in the practical application of the methods described. To this end, each chapter includes several examples of the methods proposed and Appendix A provides a broad description of E4, a free MATLAB Toolbox for time series analysis that can be freely downloaded from ucm.es/info/icae/e4. An Appendix provides the source code and data references required to replicate all the practical examples.