Time Series Analysis and Its Applications: With R Examples, 4/e (Paperback)

Robert H. Shumway, David S. Stoffer

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商品描述

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.

 

 

商品描述(中文翻譯)

這本受歡迎的研究生教科書的第四版,與前作一樣,提供了平衡且全面的時間和頻率領域方法,並附有相應的理論。大量使用非平凡數據的例子,展示了解決問題的方法,例如發現自然和人為氣候變化、使用功能性磁共振成像評估疼痛感知實驗,以及監測核試禁止條約。

本書旨在作為物理、生物和社會科學研究生的教科書,以及統計學研究生的教材。某些部分也可作為本科入門課程。理論和方法脫離,以便在不同層次上進行介紹。除了涵蓋傳統的時間序列回歸方法、ARIMA模型、頻譜分析和狀態空間模型外,本書還包括現代發展,包括類別時間序列分析、多變量頻譜方法、長記憶序列、非線性模型、重抽樣技術、GARCH模型、ARMAX模型、隨機波動性、小波和馬爾可夫鏈蒙特卡羅積分方法。

本版還包括每個數值例子的R代碼,以及附錄R,其中提供了教材中使用的數據集和R腳本的參考,以及有關基本R命令和R時間序列的教程。書的網站上還提供了一個額外的文件供下載,使所有數據集和腳本都可以輕鬆加載到R中。