Forecasting, Structural Time Series Models and the Kalman Filter

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9780521321969: Forecasting, Structural Time Series Models and the Kalman Filter

This book is concerned with modelling economic and social time series and with addressing the special problems which the treatment of such series pose. It is unique in its use of Kalman filtering with econometric and time series modelling.

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Críticas:

'... if you're looking for a state of the art monograph on applied aspects of state-space representations, and Kalman filtering ... then Harvey's book is required reading.' Econometric Theory

Reseña del editor:

In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

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1.

Harvey, Andrew C.
Editorial: Cambridge University Press (1990)
ISBN 10: 0521321964 ISBN 13: 9780521321969
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Descripción Cambridge University Press, 1990. HRD. Estado de conservación: New. New Book.Shipped from US within 10 to 14 business days.THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. de la librería IP-9780521321969

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Harvey, Andrew C.
Editorial: Cambridge University Press (1990)
ISBN 10: 0521321964 ISBN 13: 9780521321969
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Descripción Cambridge University Press, 1990. HRD. Estado de conservación: New. New Book. Delivered from our US warehouse in 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND.Established seller since 2000. Nº de ref. de la librería IP-9780521321969

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Harvey, Andrew C.
Editorial: Cambridge University Press (2016)
ISBN 10: 0521321964 ISBN 13: 9780521321969
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Descripción Cambridge University Press, 2016. Paperback. Estado de conservación: New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. Nº de ref. de la librería ria9780521321969_lsuk

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Harvey, Andrew C.
Editorial: Cambridge Univ Pr (1990)
ISBN 10: 0521321964 ISBN 13: 9780521321969
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Descripción Cambridge Univ Pr, 1990. Hardcover. Estado de conservación: Brand New. 1st edition. 570 pages. 9.06x6.22x1.65 inches. In Stock. Nº de ref. de la librería __0521321964

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ANDREW C. HARVEY
ISBN 10: 0521321964 ISBN 13: 9780521321969
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Descripción 1990. Hardback. Estado de conservación: NEW. 9780521321969 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Nº de ref. de la librería HTANDREE0439654

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Andrew C. Harvey
Editorial: Cambridge University Press 1990-02-22 (1990)
ISBN 10: 0521321964 ISBN 13: 9780521321969
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Descripción Cambridge University Press 1990-02-22, 1990. Estado de conservación: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely. Nº de ref. de la librería NU-ING-00913828

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Andrew C. Harvey
Editorial: Cambridge University Press
ISBN 10: 0521321964 ISBN 13: 9780521321969
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Descripción Cambridge University Press. Hardcover. Estado de conservación: New. This item is printed on demand. Hardcover. 572 pages. This book provides a synthesis of concepts and materials that ordinarily appear separately in time series and econometrics literature, presenting a comprehensive review of both theoretical and applied concepts. Perhaps the most novel feature of the book is its use of Kalman filtering together with econometric and time series methodology. From a technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. This technique was originally developed in control engineering but is becoming increasingly important in economics and operations research. The book is primarily concerned with modeling economic and social time series and with addressing the special problems that the treatment of such series pose. This item ships from La Vergne,TN. Hardcover. Nº de ref. de la librería 9780521321969

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Harvey, Andrew C.
Editorial: Cambridge University Press (1990)
ISBN 10: 0521321964 ISBN 13: 9780521321969
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Descripción Cambridge University Press, 1990. Hardcover. Estado de conservación: New. Nº de ref. de la librería INGM9780521321969

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A.C. Harvey
Editorial: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2009)
ISBN 10: 0521321964 ISBN 13: 9780521321969
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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2009. Hardback. Estado de conservación: New. Reprint. 230 x 158 mm. Language: English . Brand New Book ***** Print on Demand *****.In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK. Nº de ref. de la librería APC9780521321969

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10.

A.C. Harvey
Editorial: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2009)
ISBN 10: 0521321964 ISBN 13: 9780521321969
Nuevos Tapa dura Cantidad: 10
Impresión bajo demanda
Librería
The Book Depository US
(London, Reino Unido)
Valoración
[?]

Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2009. Hardback. Estado de conservación: New. Reprint. 230 x 158 mm. Language: English . Brand New Book ***** Print on Demand *****. In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK. Nº de ref. de la librería APC9780521321969

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