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Cover: 9783319524511 | Time Series Analysis and Its Applications | With R Examples | Buch
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Time Series Analysis and Its Applications
With R Examples
Taschenbuch von David S. Stoffer (u. a.)
Sprache: Englisch

115,95 €*

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Beschreibung
The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty.
The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, ARMAX models, stochastic volatility, wavelets, and Markov chain Monte Carlo integration methods.

This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series. An additional file is available on the book¿s website for download, making all the data sets and scripts easy to load into R.
The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty.
The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, ARMAX models, stochastic volatility, wavelets, and Markov chain Monte Carlo integration methods.

This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series. An additional file is available on the book¿s website for download, making all the data sets and scripts easy to load into R.
Über den Autor
Robert H. Shumway, PhD, is Professor Emeritus of Statistics at the University of California, Davis. He is a Fellow of the American Statistical Association and a member of the International Statistical Institute. He won the 1986 American Statistical Association Award for Outstanding Statistical Application and the 1992 Communicable Diseases Center Statistics Award; both awards were for joint papers on time series applications. He is also the author of a Prentice-Hall text on applied time series analysis and served as a Departmental Editor for the Journal of Forecasting and Associate Editor for the Journal of the American Statistical Association.

David S. Stoffer, PhD, is Professor of Statistics at the University of Pittsburgh. He is a Fellow of the American Statistical Association and has made seminal contributions to the analysis of categorical time series. David won the 1989 American Statistical Association Award for Outstanding Statistical Application in a joint paper analyzing categorical time series arising in infant sleep-state cycling. He is currently a Departmental Editor of the Journal of Forecasting and an Associate Editor of the Annals of Statistical Mathematics. He has served as Program Director in the Division of Mathematical Sciences at the National Science Foundation and as Associate Editor for the Journal of the American Statistical Association.


Inhaltsverzeichnis
1. Characteristics of Time Series.- 2. Time Series Regression and Exploratory Data Analysis.- 3. ARIMA Models.- 4. Spectral Analysis and Filtering.- 5. Additional Time Domain Topics.- 6. State-Space Models.- 7. Statistical Methods in the Frequency Domain.- 8. Appendix A: Large Sample Theory.- Appendix B: Time Domain Theory.- Appendix C: Spectral Domain Theory.- Appendix R: R Supplement.
Details
Erscheinungsjahr: 2017
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Reihe: Springer Texts in Statistics
Inhalt: xiii
562 S.
78 s/w Illustr.
70 farbige Illustr.
562 p. 148 illus.
70 illus. in color.
ISBN-13: 9783319524511
ISBN-10: 3319524518
Sprache: Englisch
Herstellernummer: 978-3-319-52451-1
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Stoffer, David S.
Shumway, Robert H.
Auflage: Fourth Edition 2017
Hersteller: Springer International Publishing
Springer International Publishing AG
Springer Texts in Statistics
Maße: 235 x 155 x 31 mm
Von/Mit: David S. Stoffer (u. a.)
Erscheinungsdatum: 19.04.2017
Gewicht: 0,861 kg
Artikel-ID: 108925065
Über den Autor
Robert H. Shumway, PhD, is Professor Emeritus of Statistics at the University of California, Davis. He is a Fellow of the American Statistical Association and a member of the International Statistical Institute. He won the 1986 American Statistical Association Award for Outstanding Statistical Application and the 1992 Communicable Diseases Center Statistics Award; both awards were for joint papers on time series applications. He is also the author of a Prentice-Hall text on applied time series analysis and served as a Departmental Editor for the Journal of Forecasting and Associate Editor for the Journal of the American Statistical Association.

David S. Stoffer, PhD, is Professor of Statistics at the University of Pittsburgh. He is a Fellow of the American Statistical Association and has made seminal contributions to the analysis of categorical time series. David won the 1989 American Statistical Association Award for Outstanding Statistical Application in a joint paper analyzing categorical time series arising in infant sleep-state cycling. He is currently a Departmental Editor of the Journal of Forecasting and an Associate Editor of the Annals of Statistical Mathematics. He has served as Program Director in the Division of Mathematical Sciences at the National Science Foundation and as Associate Editor for the Journal of the American Statistical Association.


Inhaltsverzeichnis
1. Characteristics of Time Series.- 2. Time Series Regression and Exploratory Data Analysis.- 3. ARIMA Models.- 4. Spectral Analysis and Filtering.- 5. Additional Time Domain Topics.- 6. State-Space Models.- 7. Statistical Methods in the Frequency Domain.- 8. Appendix A: Large Sample Theory.- Appendix B: Time Domain Theory.- Appendix C: Spectral Domain Theory.- Appendix R: R Supplement.
Details
Erscheinungsjahr: 2017
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Reihe: Springer Texts in Statistics
Inhalt: xiii
562 S.
78 s/w Illustr.
70 farbige Illustr.
562 p. 148 illus.
70 illus. in color.
ISBN-13: 9783319524511
ISBN-10: 3319524518
Sprache: Englisch
Herstellernummer: 978-3-319-52451-1
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Stoffer, David S.
Shumway, Robert H.
Auflage: Fourth Edition 2017
Hersteller: Springer International Publishing
Springer International Publishing AG
Springer Texts in Statistics
Maße: 235 x 155 x 31 mm
Von/Mit: David S. Stoffer (u. a.)
Erscheinungsdatum: 19.04.2017
Gewicht: 0,861 kg
Artikel-ID: 108925065
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