Optimal Reconciliation

Optimal Reconciliation is a hierarchical forecasting method that belongs to the class of reconciliation approaches by minimizing the expected forecast error across all levels of a hierarchy through a statistically justified combination of base forecasts using a weighting scheme derived from the covariance structure of the errors.

10

Publications

498

Citations

24

Authors

12

Institutions

Publications per year

2017–2026

5

Authors

24

  1. RJ
    Rob J. Hyndman

    Monash University, Australia

    3 publications · 369 citations

    3

    h-index

  2. GA
    George Athanasopoulos

    Monash University, Australia

    2 publications · 337 citations

    2

    h-index

  3. SL
    Shanika L. Wickramasuriya

    University of Auckland, New Zealand

    2 publications · 336 citations

    2

    h-index

  4. YK
    Yanfei Kang

    Beihang University, China

    1 publications · 17 citations

    1

    h-index

  5. AL
    Anthony Leverrier

    Institut national de recherche en sciences et technologies du numérique, France

    1 publications · 22 citations

    1

    h-index

1–5 of 24

Venues

  1. HAL (Le Centre pour la Communication Scientifique Directe)

    Repository · 1 publications · 16 citations

    1

    h-index

  2. 72nd EAGE Conference and Exhibition incorporating SPE EUROPEC 2010

    Conference · 1 publications · 10 citations

    1

    h-index

  3. Energies

    1 publications · 18 citations

    1

    h-index

  4. Statistics and Computing

    1 publications · 32 citations

    1

    h-index

  5. European Journal of Operational Research

    1 publications · 17 citations

    1

    h-index

1–5