Forecast Reconciliation

Forecast Reconciliation is a post-processing methodology in demand and revenue forecasting that transforms a set of incoherent base forecasts for related series—typically linked by hierarchical or grouped aggregation structures—into an adjusted set of coherent forecasts that satisfy the aggregation constraints while optimally preserving the information content of the original forecasts.

36

Publications

1.6K

Citations

60

Authors

36

Institutions

Publications per year

2017–2026

31

Authors

60

  1. RJ
    Rob J. Hyndman

    Monash University, Australia

    9 publications · 715 citations

    9

    h-index

  2. AP
    Anastasios Panagiotelis

    Monash University, Australia

    6 publications · 313 citations

    6

    h-index

  3. GA
    George Athanasopoulos

    Monash University, Australia

    5 publications · 509 citations

    5

    h-index

  4. FP
    Fotios Petropoulos

    University of Bath, United Kingdom

    4 publications · 153 citations

    4

    h-index

  5. JK
    Jan Kloppenborg Møller

    Technical University of Denmark, Denmark

    3 publications · 92 citations

    3

    h-index

1–5 of 60

Venues

  1. Solar Energy

    4 publications · 175 citations

    4

    h-index

  2. European Journal of Operational Research

    4 publications · 191 citations

    4

    h-index

  3. International Journal of Forecasting

    3 publications · 128 citations

    3

    h-index

  4. Applied Energy

    2 publications · 45 citations

    2

    h-index

  5. Energy

    1 publications · 13 citations

    1

    h-index

1–5