Smoothing Parameters

Smoothing Parameters is a set of scalar coefficients within an exponential smoothing model that governs the weighting decay of past observations in forecasting, distinguishing it as the mechanism determining the responsiveness to historical data trends and level adjustments.

317

Publications

39.8K

Citations

575

Authors

346

Institutions

Publications per year

2017–2026

51

Authors

575

  1. ES
    Everette S. Gardner

    University of Houston, United States

    6 publications · 2.5K citations

    6

    h-index

  2. JS
    Jeffrey S. Racine

    McMaster University, Canada

    5 publications · 1K citations

    5

    h-index

  3. RJ
    Rob J. Hyndman

    Monash University, Australia

    4 publications · 1.5K citations

    4

    h-index

  4. GR
    George R. Terrell

    Rice University, United States

    4 publications · 891 citations

    4

    h-index

  5. KB
    K. B. Kulasekera

    Clemson University, United States

    4 publications · 207 citations

    4

    h-index

1–5 of 575

Venues

  1. Journal of the American Statistical Association

    32 publications · 7.8K citations

    28

    h-index

  2. International Journal of Forecasting

    18 publications · 3.8K citations

    16

    h-index

  3. Journal of Computational and Graphical Statistics

    JCGS · 9 publications · 340 citations

    9

    h-index

  4. The Annals of Statistics

    7 publications · 335 citations

    7

    h-index

  5. Management Science

    6 publications · 549 citations

    6

    h-index

1–5