商品描述
The goals of this new, second edition of this book are to develop the skills and an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing dependent data. An expanded feature of this edition is the inclusion of many nontrivial data sets illustrating the wealth of potential applications to problems in the biological, physical, and social sciences as well as in economics and medicine.
This edition emphasizes a variety of methodological techniques to illustrate solutions to data analysis 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.
Key Features:
- Presents a balanced and comprehensive treatment of both time and frequency domain methods with an emphasis on data analysis.
- Detailed R code is included with each numerical example.
- Includes nontrivial data sets.
The book 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 and statistics skills, and math skills at the high school level. All the numerical examples use the R statistical package without assuming the reader has previously used the software.
商品描述(中文翻譯)
這本書的新第二版的目標是培養技能並欣賞現代時間序列分析作為分析依賴數據的工具的豐富性和多樣性。本版的一個擴展特點是包含了許多非平凡的數據集，這些數據集展示了在生物學、物理學、社會科學、經濟學和醫學等問題上的潛在應用的豐富性。
本版強調多種方法論技術，以說明解決數據分析問題的方案，例如發現自然和人為的氣候變化、使用功能性磁共振成像評估疼痛感知實驗，以及經濟和金融問題的分析。
主要特點：
- 提供時間和頻率域方法的平衡和全面的處理，重點在於數據分析。
- 每個數值範例都包含詳細的 R 代碼。
- 包含非平凡的數據集。
本書可用於一學期/一季的入門時間序列課程，前提條件是理解線性回歸、基本微積分概率和統計技能，以及高中水平的數學技能。所有數值範例均使用 R 統計套件，並不假設讀者之前已使用過該軟體。
作者簡介
Robert H. Shumway was Professor of Statistics, University of California, Davis. He was a Fellow of the American Statistical Association and won the American Statistical Association Award for Outstanding Statistical Application. He was 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 Emeritus 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 was 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. The authors have also published the more advanced Time Series Analysis and Its Application: With R Examples, Fifth Edition.
作者簡介(中文翻譯)
羅伯特·H·舒姆威是加州大學戴維斯分校的統計學教授。他是美國統計學會的會士，並獲得美國統計學會傑出統計應用獎。他著有多本教科書，並曾擔任《預測期刊》（Journal of Forecasting）和《美國統計學會期刊》（Journal of the American Statistical Association）的編輯委員會成員。
大衛·S·斯托佛是匹茲堡大學的名譽教授。他是美國統計學會的會士，並獲得美國統計學會傑出統計應用獎。他曾擔任《預測期刊》（Journal of Forecasting）、《統計數學年鑑》（Annals of Statistical Mathematics）和《時間序列分析期刊》（Journal of Time Series Analysis）的編輯委員會成員。他曾在國家科學基金會的數學科學部擔任計畫主任，並擔任《美國統計學會期刊》（Journal of the American Statistical Association）和《商業與經濟統計期刊》（Journal of Business & Economic Statistics）的副編輯。作者們還出版了更高級的《時間序列分析及其應用：R範例，第五版》（Time Series Analysis and Its Application: With R Examples, Fifth Edition）。
