Time Series Analysis and Its Applications: With R Examples (Springer Texts in Statistics) - Tapa blanda

Libro 83 de 103: Springer Texts in Statistics

Shumway, Robert H.; Stoffer, David S.

 
9783319524511: Time Series Analysis and Its Applications: With R Examples (Springer Texts in Statistics)
Tapa blanda
ISBN 10: 3319524518 ISBN 13: 9783319524511
Editorial: Springer, 2017

Sinopsis

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.


"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del 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.

De la contraportada

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.

  • Student-tested and improved
  • Accessible and complete treatment of modern time series analysis
  • Promotes understanding of theoretical concepts by bringing them into a more practical context
  • Comprehensive appendices covering the necessities of understanding the mathematics of time series analysis
  • Instructor's Manual available for adopters

New to this edition:

  • Introductions to each chapter replaced with one-page abstracts
  • All graphics and plots redone and made uniform in style
  • Bayesian section completely rewritten, covering linear Gaussian state space models only
  • R code for each example provided directly in the text for ease of data analysis replication
  • Expanded appendices with tutorials containing basic R and R time series commands
  • Data sets and additional R scripts available for download on Springer.com
  • Internal online links to every reference (equations, examples, chapters, etc.)

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2017
Idioma
Inglés
ISBN 10 
3319524518
ISBN 13 
9783319524511
Encuadernación
Tapa blanda
Número de edición
4
Número de páginas
578
Contacto del fabricante
Springer Nature Customer Service Center GmbH
ProductSafety@springernature.com

Europaplatz 3,69115 Heidelberg, Germany
Heidelberg
69115
Alemania

Otras ediciones populares con el mismo título

9780387989501: Time series analysis and its applications (Springer Texts in Statistics)

Edición Destacada

ISBN 10:  0387989501 ISBN 13:  9780387989501
Editorial: Springer Verlag, 2000
Tapa dura