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Synopsis
This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic.
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- PublisherSpringer
- Publication date1993
- ISBN 10 3540569405
- ISBN 13 9783540569404
- BindingPerfect Paperback
- LanguageEnglish
- Edition number2
- Number of pages566
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Introduction to Multiple Time Series Analysis
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Introduction to Multiple Time Series Analysis.
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Springer Verlag, Berlin, 1993
ISBN 10: 3540569405
ISBN 13: 9783540569404
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Introduction to Multiple Time Series Analysis
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Introduction to Multiple Time Series Analysis
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Springer Berlin Heidelberg Aug 1993, 1993
ISBN 10: 3540569405
ISBN 13: 9783540569404
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic. 568 pp. Englisch. Seller Inventory # 9783540569404
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Introduction to Multiple Time Series Analysis
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Springer Berlin Heidelberg, 1993
ISBN 10: 3540569405
ISBN 13: 9783540569404
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic. Seller Inventory # 9783540569404
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Introduction To Multiple Time Series Analysis
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Introduction To Multiple Time Series Analysis
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Introduction to Multiple Time Series Analysis
Published by
Springer Berlin Heidelberg, 1993
ISBN 10: 3540569405
ISBN 13: 9783540569404
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This graduate level textbook deals with analyzing and forecasting multiple time series. The models discussed include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simulta. Seller Inventory # 4894125
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Introduction to Multiple Time Series Analysis
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Introduction to Multiple Time Series Analysis
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Condition: New. pp. 568 67:B&W 6.69 x 9.61 in or 244 x 170 mm (Pinched Crown) Perfect Bound on White w/Gloss Lam. Seller Inventory # 7531963
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