Box-jenkins Methodology

Box-Jenkins Methodology is a systematic statistical modeling framework for time series analysis and forecasting, distinguished by its iterative approach involving model identification, parameter estimation, and diagnostic checking within the class of autoregressive integrated moving average (ARIMA) models.

637

Publications

36.8K

Citations

1.5K

Authors

670

Institutions

Publications per year

2017–2026

135

Variants

Box-jenkins Approach

Authors

1.5K

  1. PN
    Paul Newbold

    University of Nottingham, United Kingdom

    6 publications · 1.1K citations

    6

    h-index

  2. TN
    Thor Norström

    Stockholm University, Sweden

    6 publications · 319 citations

    6

    h-index

  3. RP
    Rik Pintelon

    Vrije Universiteit Brussel, Belgium

    5 publications · 167 citations

    5

    h-index

  4. PC
    Peter Christoffersen

    University of Toronto, Canada

    5 publications · 172 citations

    5

    h-index

  5. FX
    Francis X. Diebold

    University of Pennsylvania, United States

    5 publications · 172 citations

    5

    h-index

1–5 of 1.5K

Venues

  1. Journal of Forecasting

    18 publications · 1.4K citations

    16

    h-index

  2. Journal of the American Statistical Association

    13 publications · 1.6K citations

    12

    h-index

  3. Journal of Marketing Research

    11 publications · 705 citations

    10

    h-index

  4. Addiction

    10 publications · 797 citations

    10

    h-index

  5. SSRN Electronic Journal

    Repository · 9 publications · 200 citations

    9

    h-index

1–5