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Sinopsis
This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms for implementing the theory. In particular, it investigates the relationship between VARMA and state space models, including canonical forms. It also highlights the relationship between Wiener-Kolmogorov and Kalman filtering both with an infinite and a finite sample. The strength of the book also lies in the numerous algorithms included for state space models that take advantage of the recursive nature of the models. Many of these algorithms can be made robust, fast, reliable and efficient. The book is accompanied by a MATLAB package called SSMMATLAB and a webpage presenting implemented algorithms with many examples and case studies. Though it lays a solid theoretical foundation, the book also focuses on practical application, and includes exercises in each chapter. It is intended for researchers and students working with linear state space models, and who are familiar with linear algebra and possess some knowledge of statistics.
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Acerca del autor
Dr. Víctor Gómez is a statistician and technical advisor at the Spanish Ministry of Finance and Public Administrations in Madrid. His professional activity involves statistical, econometric and, above all, time series analysis of macroeconomic data, mostly in connection with short term economic analysis. More recently, he has focused on research in the field of time series analysis and the development of software for time series analysis. He has also taught numerous courses on time series analysis and related topics such as short-term forecasting, seasonal adjustment methods or time series filtering.
De la contraportada
This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms for implementing the theory. In particular, it investigates the relationship between VARMA and state space models, including canonical forms. It also highlights the relationship between Wiener-Kolmogorov and Kalman filtering both with an infinite and a finite sample. The strength of the book also lies in the numerous algorithms included for state space models that take advantage of the recursive nature of the models. Many of these algorithms can be made robust, fast, reliable and efficient. The book is accompanied by a MATLAB package called SSMMATLAB and a webpage presenting implemented algorithms with many examples and case studies. Though it lays a solid theoretical foundation, the book also focuses on practical application, and includes exercises in each chapter. It is intended for researchers and students working with linear state space models, and who are familiar with linear algebra and possess some knowledge of statistics.
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- EditorialSpringer
- Año de publicación2016
- ISBN 10 331928598X
- ISBN 13 9783319285986
- EncuadernaciónTapa dura
- IdiomaInglés
- Número de edición1
- Número de páginas560
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Multivariate Time Series With Linear State Space Structure.
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Cham, Springer., 2016
ISBN 10: 331928598X
ISBN 13: 9783319285986
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XVII, 541 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch. Nº de ref. del artículo: 95MB
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Multivariate Time Series With Linear State Space Structure
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Springer International Publishing, 2016
ISBN 10: 331928598X
ISBN 13: 9783319285986
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a comprehensive account of both theory and algorithms for time series and linear state space modelsRefers to a webpage with algorithms programmed in MATLAB and numerous examples Studies the relationship between VARMA and sta. Nº de ref. del artículo: 105407661
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Multivariate Time Series With Linear State Space Structure
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Springer International Publishing Mai 2016, 2016
ISBN 10: 331928598X
ISBN 13: 9783319285986
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms for implementing the theory. In particular, it investigates the relationship between VARMA and state space models, including canonical forms. It also highlights the relationship between Wiener-Kolmogorov and Kalman filtering both with an infinite and a finite sample. The strength of the book also lies in the numerous algorithms included for state space models that take advantage of the recursive nature of the models. Many of these algorithms can be made robust, fast, reliable and efficient. The book is accompanied by a MATLAB package called SSMMATLAB and a webpage presenting implemented algorithms with many examples and case studies. Though it lays a solid theoretical foundation, the book also focuses on practical application, and includes exercises in each chapter. It is intended for researchers and students working with linear state space models, and who are familiar with linear algebra and possess some knowledge of statistics. 560 pp. Englisch. Nº de ref. del artículo: 9783319285986
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Multivariate Time Series With Linear State Space Structure
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Springer International Publishing, 2016
ISBN 10: 331928598X
ISBN 13: 9783319285986
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms for implementing the theory. In particular, it investigates the relationship between VARMA and state space models, including canonical forms. It also highlights the relationship between Wiener-Kolmogorov and Kalman filtering both with an infinite and a finite sample. The strength of the book also lies in the numerous algorithms included for state space models that take advantage of the recursive nature of the models. Many of these algorithms can be made robust, fast, reliable and efficient. The book is accompanied by a MATLAB package called SSMMATLAB and a webpage presenting implemented algorithms with many examples and case studies. Though it lays a solid theoretical foundation, the book also focuses on practical application, and includes exercises in each chapter. It is intendedfor researchers and students working with linear state space models, and who are familiar with linear algebra and possess some knowledge of statistics. Nº de ref. del artículo: 9783319285986
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Multivariate Time Series With Linear State Space Structure
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Multivariate Time Series With Linear State Space Structure
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Multivariate Time Series With Linear State Space Structure
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Hardcover. Condición: Like New. Like New. book. Nº de ref. del artículo: ERICA790331928598X6
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Multivariate Time Series With Linear State Space Structure
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Springer International Publishing, Springer International Publishing Mai 2016, 2016
ISBN 10: 331928598X
ISBN 13: 9783319285986
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Neuware -This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms for implementing the theory. In particular, it investigates the relationship between VARMA and state space models, including canonical forms. It also highlights the relationship between Wiener-Kolmogorov and Kalman filtering both with an infinite and a finite sample. The strength of the book also lies in the numerous algorithms included for state space models that take advantage of the recursive nature of the models. Many of these algorithms can be made robust, fast, reliable and efficient. The book is accompanied by a MATLAB package called SSMMATLAB and a webpage presenting implemented algorithms with many examples and case studies. Though it lays a solid theoretical foundation, the book also focuses on practical application, and includes exercises in each chapter. It is intendedfor researchers and students working with linear state space models, and who are familiar with linear algebra and possess some knowledge of statistics.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 560 pp. Englisch. Nº de ref. del artículo: 9783319285986
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Multivariate Time Series With Linear State Space Structure
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Multivariate Time Series With Linear State Space Structure
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