Functional Forecasting

Functional Forecasting is a statistical prediction methodology that extends scalar and multivariate time series forecasting to the domain of infinite-dimensional functional data, where observations are trajectories or curves over a continuum, enabling the modeling and forecasting of entire functions as units rather than discrete points.

57

Publications

2.7K

Citations

101

Authors

72

Institutions

Publications per year

2017–2026

19

Authors

101

  1. HL
    Han Lin Shang

    Australian National University, Australia

    12 publications · 567 citations

    12

    h-index

  2. WJ
    Wolfgang Jank

    University of Maryland, College Park, United States

    4 publications · 259 citations

    4

    h-index

  3. PD
    P.K. Dash

    Siksha O Anusandhan University, India

    3 publications · 60 citations

    3

    h-index

  4. MJ
    Mariano J. Valderrama

    Universidad de Granada, Spain

    3 publications · 76 citations

    3

    h-index

  5. NZ
    Natasha Zhang Foutz

    University of Virginia, United States

    3 publications · 129 citations

    3

    h-index

1–5 of 101

Venues

  1. The Annals of Applied Statistics

    AOAS · 4 publications · 270 citations

    4

    h-index

  2. Journal of Forecasting

    2 publications · 71 citations

    2

    h-index

  3. Journal of Multivariate Analysis

    2 publications · 88 citations

    2

    h-index

  4. Energies

    2 publications · 94 citations

    2

    h-index

  5. Environmetrics

    2 publications · 142 citations

    2

    h-index

1–5