Time Series: A Data Analysis Approach Using R: Chapman & Hall/CRC Texts in Statistical Science
Autor Robert Shumway, David Stofferen Limba Engleză Hardback – 21 mai 2019
Numerous examples using data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and the analysis of economic and financial problems. The text can be used for a one semester/quarter introductory time series course where the prerequisites are an understanding of linear regression, basic calculus-based probability skills, and math skills at the high school level. All of the numerical examples use the R statistical package without assuming that the reader has previously used the software.
Robert H. Shumway is Professor Emeritus of Statistics, University of California, Davis. He is a Fellow of the American Statistical Association and has won the American Statistical Association Award for Outstanding Statistical Application. He is the author of numerous texts and served on editorial boards such as the Journal of Forecasting and the Journal of the American Statistical Association.
David S. Stoffer is Professor of Statistics, University of Pittsburgh. He is a Fellow of the American Statistical Association and has won the American Statistical Association Award for Outstanding Statistical Application. He is currently on the editorial boards of the Journal of Forecasting, the Annals of Statistical Mathematics, and the Journal of Time Series Analysis. He served as a Program Director in the Division of Mathematical Sciences at the National Science Foundation and as an Associate Editor for the Journal of the American Statistical Association and the Journal of Business & Economic Statistics.
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Specificații
ISBN-13: 9780367221096
ISBN-10: 0367221098
Pagini: 272
Dimensiuni: 156 x 234 x 16 mm
Greutate: 0.43 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Texts in Statistical Science
ISBN-10: 0367221098
Pagini: 272
Dimensiuni: 156 x 234 x 16 mm
Greutate: 0.43 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Texts in Statistical Science
Cuprins
1. Time Series Characteristics.
2. Time Series Regression and EDA.
3. ARIMA Models.
4. Spectral Analysis and Filtering.
5. Some Additional Topics.
2. Time Series Regression and EDA.
3. ARIMA Models.
4. Spectral Analysis and Filtering.
5. Some Additional Topics.
Notă biografică
Robert H. Shumway is Professor Emeritus of Statistics, University of California, Davis. He is a Fellow of the American Statistical Association and has won the American Statistical Association Award for Outstanding Statistical Application. He is the author of numerous texts and served on editorial boards such as the Journal of Forecasting and the Journal of the American Statistical Association.David S. Stoffer is Professor of Statistics, University of Pittsburgh. He is a Fellow of the American Statistical Association and has won the American Statistical Association Award for Outstanding Statistical Application. He is currently on the editorial boards of the Journal of Forecasting, the Annals of Statistical Mathematics, and the Journal of Time Series Analysis. He served as a Program Director in the Division of Mathematical Sciences at the National Science Foundation and as an Associate Editor for the Journal of the American Statistical Association and the Journal of Business & Economic Statistics.
Recenzii
"The intended audience of the book are mathematics undergraduates taking a one semester course on time series. . . The authors frame learning time series primarily by extending concepts from linear models. Personally, I favour this approach, since it allows the book to clearly signpost similarities and differences between concepts in both topics and provides a natural learning progression from what most undergraduate students will already be familiar with . . .This book successfully delivers a practical tool-based approach to time series analysis at an introductory level, complementing the existing texts from the authors, which are aimed at a more advanced audience."
~Matthew Nunes, Journal Times Series Analysis
~Matthew Nunes, Journal Times Series Analysis
Descriere
This textbook is designed for an introductory time series course where the prerequisites are an understanding of linear regression and some basic probability skills. All of the numerical examples were done using the R statistical package, and the code is typically listed at the end of an example.