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＜電子ブック＞
Analysis of Integrated and Cointegrated Time Series with R / by Bernhard Pfaff
(Use R!. ISSN:21975744)

版	2nd ed. 2008.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	2008
本文言語	英語
大きさ	XX, 190 p : online resource
著者標目	*Pfaff, Bernhard author SpringerLink (Online service)
件　名	LCSH:Econometrics LCSH:Statistics  LCSH:Probabilities LCSH:Computer science -- Mathematics  全ての件名で検索 LCSH:Mathematical statistics FREE:Econometrics FREE:Statistical Theory and Methods FREE:Probability Theory FREE:Probability and Statistics in Computer Science
一般注記	Theoretical Concepts -- Univariate Analysis of Stationary Time Series -- Multivariate Analysis of Stationary Time Series -- Non-stationary Time Series -- Cointegration -- Unit Root Tests -- Testing for the Order of Integration -- Further Considerations -- Cointegration -- Single-Equation Methods -- Multiple-Equation Methods The analysis of integrated and co-integrated time series can be considered as the main methodology employed in applied econometrics. This book not only introduces the reader to this topic but enables him to conduct the various unit root tests and co-integration methods on his own by utilizing the free statistical programming environment R. The book encompasses seasonal unit roots, fractional integration, coping with structural breaks, and multivariate time series models. The book is enriched by numerous programming examples to artificial and real data so that it is ideally suited as an accompanying text book to computer lab classes. The second edition adds a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models. To analyze the interactions between the investigated variables, further impulse response function and forecast error variance decompositions are introduced as well as forecasting. The author explains how these model types relate to each other HTTP:URL=https://doi.org/10.1007/978-0-387-75967-8

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