Introduction to Time Series Analysis & Forecasting, 3/e (Hardcover)

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

Introduction to Time Series Analysis & Forecasting, 3/e (Hardcover)
  • 出版商: Wiley
  • 出版日期: 2024-06-01
  • 定價: $1,780
  • 售價: 9.8 折 $1,744
  • 語言: 英文
  • 頁數: 736
  • ISBN: 139418669X
  • ISBN-13: 9781394186693

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商品描述

Bring the latest statistical tools to bear on predicting future variables and outcomes

A huge range of fields rely on forecasts of how certain variables and causal factors will affect future outcomes, from product sales to inflation rates to demographic changes. Time series analysis is the branch of applied statistics which generates forecasts, and its sophisticated use of time oriented data can vastly impact the quality of crucial predictions. The latest computing and statistical methodologies are constantly being sought to refine these predictions and increase the confidence with which important actors can rely on future outcomes.

Time Series Analysis and Forecasting presents a comprehensive overview of the methodologies required to produce these forecasts with the aid of time-oriented data sets. The potential applications for these techniques are nearly limitless, and this foundational volume has now been updated to reflect the most advanced tools. The result, more than ever, is an essential introduction to a core area of statistical analysis.

Readers of the third edition of Time Series Analysis and Forecasting will also find:

  • Updates incorporating JMP, SAS, and R software, with new examples throughout
  • Over 300 exercises and 50 programming algorithms that balance theory and practice
  • Supplementary materials in the e-book including solutions to many problems, data sets, and brand-new explanatory videos covering the key concepts and examples from each chapter.

Time Series Analysis and Forecasting is ideal for graduate and advanced undergraduate courses in the areas of data science and analytics and forecasting and time series analysis. It is also an outstanding reference for practicing data scientists.

商品描述(中文翻譯)

將最新的統計工具應用於預測未來變數和結果

許多領域依賴於對某些變數和因果因素如何影響未來結果的預測，從產品銷售到通脹率再到人口變化。時間序列分析是應用統計學的一個分支，專門用於生成預測，其對時間導向數據的精細使用可以大幅影響關鍵預測的質量。最新的計算和統計方法不斷被尋求，以精煉這些預測並提高重要參與者對未來結果的信心。

《時間序列分析與預測》提供了所需方法論的全面概述，以利用時間導向數據集來生成這些預測。這些技術的潛在應用幾乎是無限的，這本基礎性著作現在已更新，以反映最先進的工具。結果是，這本書比以往任何時候都更是統計分析核心領域的重要入門書籍。

第三版《時間序列分析與預測》的讀者還將發現：

- 包含JMP、SAS和R軟體的更新，並在全書中提供新的範例
- 超過300個練習題和50個編程算法，平衡理論與實踐
- 電子書中的補充材料，包括許多問題的解答、數據集，以及全新解釋性視頻，涵蓋每章的關鍵概念和範例。

《時間序列分析與預測》非常適合研究生和高年級本科生的數據科學、分析、預測和時間序列分析課程。它也是實踐數據科學家的優秀參考書。

作者簡介

Douglas C. Montgomery, PhD, is Regents Professor of Industrial Engineering and ASU Foundation Professor of Engineering at Arizona State University, USA. He holds a PhD in Engineering from Virginia Tech and has researched and published extensively on industrial statistics and experimental design.

Cheryl Jennings, PhD, is Associate Teaching Professor at Arizona State University. She has decades of industrial experience in manufacturing and financial services, and has taught undergraduate and graduate courses on modeling and analysis, performance management, process control, and related subjects.

Murat Kulahci, PhD, is Professor of Industrial Statistics at the Technical University of Denmark and Professor at the Luleå University of Technology, Sweden. He holds a PhD in Industrial Engineering from the University of Wisconsin, Madison. He has published widely on time series analysis, experimental design, process monitoring and related subjects.

作者簡介(中文翻譯)

道格拉斯·C·蒙哥馬利（Douglas C. Montgomery），博士，是美國亞利桑那州立大學的工業工程榮譽教授及亞利桑那州立大學基金會工程教授。他擁有維吉尼亞理工大學的工程博士學位，並在工業統計和實驗設計方面進行了廣泛的研究和出版。

謝麗爾·詹寧斯（Cheryl Jennings），博士，是亞利桑那州立大學的副教學教授。她在製造業和金融服務領域擁有數十年的工業經驗，並教授有關建模與分析、績效管理、過程控制及相關主題的本科和研究生課程。

穆拉特·庫拉赫奇（Murat Kulahci），博士，是丹麥技術大學的工業統計教授及瑞典盧勒奧科技大學的教授。他擁有威斯康辛大學麥迪遜分校的工業工程博士學位，並在時間序列分析、實驗設計、過程監控及相關主題上發表了廣泛的研究。

目錄大綱

1 Introduction to Time Series Analysis and Forecasting
2 Statistics Background for Time Series Analysis and Forecasting
3 Regression Analysis and Forecasting
4 Exponential Smoothing Methods
5 Autoregressive Integrated Moving Average (ARIMA) Models
6 Transfer Functions and Intervention Models
7 Other Time Series Analysis and Forecasting Methods
Appendix A Statistical Tables
Appendix B Data Sets for Exercises
Appendix C Introduction to R

目錄大綱(中文翻譯)

1 時間序列分析與預測導論
2 時間序列分析與預測的統計背景
3 迴歸分析與預測
4 指數平滑法
5 自回歸整合移動平均 (ARIMA) 模型
6 轉移函數與介入模型
7 其他時間序列分析與預測方法
附錄 A 統計表
附錄 B 練習用數據集
附錄 C R 語言導論

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