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Sinopsis
In this book, the author adopts a state space approach to time series modeling to provide a new, computer-oriented method for building models for vector-valued time series. This second edition has been completely reorganized and rewritten. Background material leading up to the two types of estimators of the state space models is collected and presented coherently in four consecutive chapters. New, fuller descriptions are given of state space models for autoregressive models commonly used in the econometric and statistical literature. Backward innovation models are newly introduced in this edition in addition to the forward innovation models, and both are used to construct instrumental variable estimators for the model matrices. Further new items in this edition include statistical properties of the two types of estimators, more details on multiplier analysis and identification of structural models using estimated models, incorporation of exogenous signals and choice of model size. A whole new chapter is devoted to modeling of integrated, nearly integrated and co-integrated time series.
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In this book, the author adopts a state space approach to time series modeling to provide a new, computer-oriented method for building models for vector-valued time series. This second edition has been completely reorganized and rewritten. Background material leading up to the two types of estimators of the state space models is collected and presented coherently in four consecutive chapters. New, fuller descriptions are given of state space models for autoregressive models commonly used in the econometric and statistical literature. Backward innovation models are newly introduced in this edition in addition to the forward innovation models, and both are used to construct instrumental variable estimators for the model matrices. Further new items in this edition include statistical properties of the two types of estimators, more details on multiplier analysis and identification of structural models using estimated models, incorporation of exogenous signals and choice of model size. A whole new chapter is devoted to modeling of integrated, nearly integrated and co-integrated time series.
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State Space Modeling of Time Series (Universitext)
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STATE SPACE MODELING OF TIME SERIES
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Springer-Verlag, Berlin, 1990
ISBN 10: 3540528709
ISBN 13: 9783540528708
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State Space Modeling of Time Series Universitext
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Condición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Re-bound by library. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:3540528709. Nº de ref. del artículo: 4844138
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State Space Modeling of Time Series (Paperback)
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Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 1990
ISBN 10: 3540528709
ISBN 13: 9783540528708
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Paperback. Condición: new. Paperback. The author adopts a state space approach to time series modelling in this volume to provide a new, computer-orientated method for building models for vector-valued time series. Background material leading up to the two types of estimators of the state space models is collected and presented coherently in four consecutive chapters. This edition has been revised to provide more comprehensive descriptions of state space models for autoregressive models commonly used in the econometric and statistical literature. Backward innovation models are introduced in addition to the forward innovation models, and both are used to construct instrumental variable estimators for the model matrices. Further items in this edition include statistical properties of these two types of estimators, more details on multiplier analysis and the identification of structural models using estimated models, incorporation of exogenous signals and choice of model size. A chapter is devoted to the modelling of integrated, nearly integrated and co-integrated time series. This book provides a state space approach to time series modelling. The new edition has been reorganised and rewritten. The aim of the book is to present a new, computer-oriented method for building models for vector-valued time series. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783540528708
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