Introduction to Time Series Analysis & Forecasting, 2/e (Hardcover)

Douglas C. Montgomery, Cheryl L. Jennings, Murat Kulahci

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Praise for the First Edition "...[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics." -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both popular and modern time series methodologies as well as an introduction to Bayesian methods in forecasting. Introduction to Time Series Analysis and Forecasting, Second Edition also includes: * Over 300 exercises from diverse disciplines including health care, environmental studies, engineering, and finance * More than 50 programming algorithms using JMP(R), SAS(R), and R that illustrate the theory and practicality of forecasting techniques in the context of time-oriented data * New material on frequency domain and spatial temporal data analysis * Expanded coverage of the variogram and spectrum with applications as well as transfer and intervention model functions * A supplementary website featuring PowerPoint(R) slides, data sets, and select solutions to the problems Introduction to Time Series Analysis and Forecasting, Second Edition is an ideal textbook upper-undergraduate and graduate-levels courses in forecasting and time series. The book is also an excellent reference for practitioners and researchers who need to model and analyze time series data to generate forecasts.

商品描述(中文翻譯)

第一版的好評如潮:“...[t]本書非常適合需要應用所介紹的方法和模型,但在數學和統計方面背景較少的讀者。” -MAA評論。《時間序列分析與預測入門》第二版在全書中進行了全面的更新,介紹了分析時間導向數據和構建現實世界短期到中期統計預測所需的時間序列分析的基本理論。本書由經驗豐富的工程統計學者和專業人士撰寫,包括對流行和現代時間序列方法的討論,以及對貝葉斯方法在預測中的介紹。《時間序列分析與預測入門》第二版還包括: *超過300個來自不同學科的練習,包括醫療保健、環境研究、工程和金融 *使用JMP(R)、SAS(R)和R的50多個編程算法,以在時間導向數據的背景下說明預測技術的理論和實用性 *關於頻域和時空數據分析的新材料 *對變異圖和頻譜的擴展覆蓋,包括應用以及轉移和干預模型函數 *一個補充網站,提供PowerPoint(R)幻燈片、數據集和選擇問題的解答《時間序列分析與預測入門》第二版是預測和時間序列的高年級本科和研究生課程的理想教材。本書也是需要對時間序列數據進行建模和分析以生成預測的從業人員和研究人員的優秀參考資料。