George Box's contributions to time series analysis and forecasting

被引:6
作者
Ljung, G. M.
Ledolter, J. [1 ]
Abraham, B. [2 ]
机构
[1] Univ Iowa, Dept Management Sci, Tippie Coll Business, Iowa City, IA 52242 USA
[2] Univ Waterloo, Dept Stat & Actuarial Sci, Waterloo, ON N2L 3G1, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Box; time series; forecasting; intervention analysis; outliers; multiple time series; MOVING AVERAGE MODELS; LIKELIHOOD FUNCTION; OUTLIERS; SPECIFICATION;
D O I
10.1002/asmb.2016
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
George Edward Pelham Box was born on October 19, 1919 in Gravesend, Kent, UK and died on March 28, 2013 in Madison, Wisconsin, USA. George Box made significant contributions to many fields of statistics including design of experiments and response surface methodology, evolutionary operation, statistical inference, robustness, Bayesian methods, time series analysis and forecasting, and quality improvement. Our paper discusses his contributions to time series analysis and forecasting. His work in this area started in collaboration with Gwilym Jenkins in the early 1960s and continued over the next several decades. His contributions include the classic and extraordinarily influential book Time Series Analysis: Forecasting and Control' written with Gwilym Jenkins and first published by Holden Day in 1970. Subsequent contributions to time series analysis include joint work with George Tiao, Gregory Reinsel, Daniel Pena, and many former graduate students. His work provided a unified framework for carrying out time series analysis in practice and laid the foundation for many new developments in the field. Copyright (c) 2014 John Wiley & Sons, Ltd.
引用
收藏
页码:25 / 35
页数:11
相关论文
共 50 条
  • [21] Prior Training with Jittered Series for Time Series Forecasting
    Huang, T. C.
    IEEM: 2008 INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT, VOLS 1-3, 2008, : 2001 - 2005
  • [22] Analysis and forecasting of the performance of a power plant condenser using Box-Jenkins time series and neural networks
    Montañés, E
    Menéndez, CO
    Prieto, MM
    ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, 2002, 10 (02): : 115 - 121
  • [23] Intelligent system for time series forecasting
    Proskuryakov, A.
    XII INTERNATIONAL SYMPOSIUM INTELLIGENT SYSTEMS 2016, (INTELS 2016), 2017, 103 : 363 - 369
  • [24] A Survey on Forecasting of Time Series Data
    Mahalakshmi, G.
    Sridevi, S.
    Rajaram, S.
    2016 INTERNATIONAL CONFERENCE ON COMPUTING TECHNOLOGIES AND INTELLIGENT DATA ENGINEERING (ICCTIDE'16), 2016,
  • [25] Targeted Attacks on Time Series Forecasting
    Chen, Zeyu
    Dost, Katharina
    Zhu, Xuan
    Chang, Xinglong
    Dobbie, Gillian
    Wicker, Jorg
    ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PAKDD 2023, PT IV, 2023, 13938 : 314 - 327
  • [26] Automated time series forecasting for biosurveillance
    Burkom, Howard S.
    Murphy, Sean Patrick
    Shmueli, Galit
    STATISTICS IN MEDICINE, 2007, 26 (22) : 4202 - 4218
  • [27] Efficient Forecasting for Hierarchical Time Series
    Dannecker, Lars
    Lorenz, Robert
    Roesch, Philipp
    Lehner, Wolfgang
    Hackenbroich, Gregor
    PROCEEDINGS OF THE 22ND ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM'13), 2013, : 2399 - 2404
  • [28] Forecasting time series with multivariate copulas
    Simard, Clarence
    Remillard, Bruno
    DEPENDENCE MODELING, 2015, 3 (01): : 59 - 82
  • [29] Dense Sampling of Time Series for Forecasting
    Oh, Il-Seok
    Lee, Jin-Seon
    IEEE ACCESS, 2022, 10 : 75571 - 75580
  • [30] Model Selection for Time Series Forecasting An Empirical Analysis of Multiple Estimators
    Vitor Cerqueira
    Luis Torgo
    Carlos Soares
    Neural Processing Letters, 2023, 55 : 10073 - 10091