Analysis of integrated and cointegrated time series with R / Bernhard Pfaff
Pfaff, Bernhard
Analysis of integrated and cointegrated time series with R / Bernhard Pfaff - 2nd ed. - New York : Springer, 2008 - XX, 188 p. : graf. ; 24 cm - Use R .
Índice
Bibliografía: p. [169]-175
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. Ideally suited for computer labs: Econometric theory/methods and their implementation within R is exhibited Self-contained: The book can be used for self-study; code examples are elaborated Wide audience is addressed: Upper-undergraduate/Graduate students and practitioners Índice: Univariate analysis of stationary time series.- Multivariate analysis of stationary time series.- Non-stationary time series.- Cointegration.- Testing for the order of integration.- Further considerations.- Single equation methods.- Multiple equation methods.- Appendix.- Abbreviations, nomenclature and symbols.- List of tables.- List of figures.- List of R code.- References.
978-0-387-75966-1
Análisis de series temporales
R (Lenguaje de programación)
Econometría
Estadística matemática
Probabilidades
Analysis of integrated and cointegrated time series with R / Bernhard Pfaff - 2nd ed. - New York : Springer, 2008 - XX, 188 p. : graf. ; 24 cm - Use R .
Índice
Bibliografía: p. [169]-175
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. Ideally suited for computer labs: Econometric theory/methods and their implementation within R is exhibited Self-contained: The book can be used for self-study; code examples are elaborated Wide audience is addressed: Upper-undergraduate/Graduate students and practitioners Índice: Univariate analysis of stationary time series.- Multivariate analysis of stationary time series.- Non-stationary time series.- Cointegration.- Testing for the order of integration.- Further considerations.- Single equation methods.- Multiple equation methods.- Appendix.- Abbreviations, nomenclature and symbols.- List of tables.- List of figures.- List of R code.- References.
978-0-387-75966-1
Análisis de series temporales
R (Lenguaje de programación)
Econometría
Estadística matemática
Probabilidades