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Time Series Models
Taschenbuch von Wolfgang Scherrer (u. a.)
Sprache: Englisch

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Beschreibung
This textbook provides a self-contained presentation of the theory and models of time series analysis. Putting an emphasis on weakly stationary processes and linear dynamic models, it describes the basic concepts, ideas, methods and results in a mathematically well-founded form and includes numerous examples and exercises. The first part presents the theory of weakly stationary processes in time and frequency domain, including prediction and filtering. The second part deals with multivariate AR, ARMA and state space models, which are the most important model classes for stationary processes, and addresses the structure of AR, ARMA and state space systems, Yule-Walker equations, factorization of rational spectral densities and Kalman filtering. Finally, there is a discussion of Granger causality, linear dynamic factor models and (G)ARCH models. The book provides a solid basis for advanced mathematics students and researchers in fields such as data-driven modeling, forecasting and filtering, which are important in statistics, control engineering, financial mathematics, econometrics and signal processing, among other subjects.
This textbook provides a self-contained presentation of the theory and models of time series analysis. Putting an emphasis on weakly stationary processes and linear dynamic models, it describes the basic concepts, ideas, methods and results in a mathematically well-founded form and includes numerous examples and exercises. The first part presents the theory of weakly stationary processes in time and frequency domain, including prediction and filtering. The second part deals with multivariate AR, ARMA and state space models, which are the most important model classes for stationary processes, and addresses the structure of AR, ARMA and state space systems, Yule-Walker equations, factorization of rational spectral densities and Kalman filtering. Finally, there is a discussion of Granger causality, linear dynamic factor models and (G)ARCH models. The book provides a solid basis for advanced mathematics students and researchers in fields such as data-driven modeling, forecasting and filtering, which are important in statistics, control engineering, financial mathematics, econometrics and signal processing, among other subjects.
Über den Autor

Manfred Deistler is Emeritus Professor of Econometrics and System Theory at the Institute of Statistics and Mathematical Methods in Economics at the TU Wien, Vienna, Austria. His research interests include time series analysis, systems identification and econometrics. He is a Fellow of the Econometric Society, the IEEE, and the Journal of Econometrics.

Wolfgang Scherrer is a Professor of Econometrics and System Theory at the Institute of Statistics and Mathematical Methods in Economics at the TU Wien, Vienna, Austria. His research interests include time series analysis, econometrics, dynamic factor models and applications in the area of energy supply.

Inhaltsverzeichnis

Preface.- 1 Time Series and Stationary Processes.- 2 Prediction.- 3 Spectral Representation.- 4 Filter.- 5 Autoregressive Processes.- 6 ARMA Systems and ARMA Processes.- 7 State-Space Systems.- 8 Models with Exogenous Variables.- 9 Granger Causality.- 10 Dynamic Factor Models.- 10 ARCH and GARCH Models.- Index.

Details
Erscheinungsjahr: 2022
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 216
Reihe: Lecture Notes in Statistics
Inhalt: xiv
201 S.
3 s/w Illustr.
10 farbige Illustr.
201 p. 13 illus.
10 illus. in color.
ISBN-13: 9783031132124
ISBN-10: 3031132122
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Scherrer, Wolfgang
Deistler, Manfred
Auflage: 1st ed. 2022
Hersteller: Springer International Publishing
Springer International Publishing AG
Lecture Notes in Statistics
Maße: 235 x 155 x 12 mm
Von/Mit: Wolfgang Scherrer (u. a.)
Erscheinungsdatum: 22.10.2022
Gewicht: 0,335 kg
preigu-id: 122064761
Über den Autor

Manfred Deistler is Emeritus Professor of Econometrics and System Theory at the Institute of Statistics and Mathematical Methods in Economics at the TU Wien, Vienna, Austria. His research interests include time series analysis, systems identification and econometrics. He is a Fellow of the Econometric Society, the IEEE, and the Journal of Econometrics.

Wolfgang Scherrer is a Professor of Econometrics and System Theory at the Institute of Statistics and Mathematical Methods in Economics at the TU Wien, Vienna, Austria. His research interests include time series analysis, econometrics, dynamic factor models and applications in the area of energy supply.

Inhaltsverzeichnis

Preface.- 1 Time Series and Stationary Processes.- 2 Prediction.- 3 Spectral Representation.- 4 Filter.- 5 Autoregressive Processes.- 6 ARMA Systems and ARMA Processes.- 7 State-Space Systems.- 8 Models with Exogenous Variables.- 9 Granger Causality.- 10 Dynamic Factor Models.- 10 ARCH and GARCH Models.- Index.

Details
Erscheinungsjahr: 2022
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 216
Reihe: Lecture Notes in Statistics
Inhalt: xiv
201 S.
3 s/w Illustr.
10 farbige Illustr.
201 p. 13 illus.
10 illus. in color.
ISBN-13: 9783031132124
ISBN-10: 3031132122
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Scherrer, Wolfgang
Deistler, Manfred
Auflage: 1st ed. 2022
Hersteller: Springer International Publishing
Springer International Publishing AG
Lecture Notes in Statistics
Maße: 235 x 155 x 12 mm
Von/Mit: Wolfgang Scherrer (u. a.)
Erscheinungsdatum: 22.10.2022
Gewicht: 0,335 kg
preigu-id: 122064761
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