Mean Absolute Error Analysis

Mean Absolute Error Analysis is a statistical evaluation method that quantifies the average magnitude of prediction errors by computing the mean of absolute differences between predicted and observed values, distinguishing itself from other error metrics through its linear weighting of deviations regardless of direction.

868

Publications

53.3K

Citations

3K

Authors

1.3K

Institutions

Publications per year

2017–2026

388

Authors

3K

  1. YN
    Y. Neuvo

    9 publications · 253 citations

    9

    h-index

  2. EJ
    Edward J. Coyle

    Purdue University West Lafayette, United States

    6 publications · 476 citations

    6

    h-index

  3. MG
    Moncef Gabbouj

    6 publications · 199 citations

    6

    h-index

  4. AA
    Alexander A. Voityuk

    Universitat de Girona, Spain

    4 publications · 440 citations

    4

    h-index

  5. LB
    Leonid B. Krivdin

    A.E. Favorsky Irkutsk Institute of Chemistry, Russia

    4 publications · 61 citations

    4

    h-index

1–5 of 3K

Venues

  1. The Journal of Chemical Physics

    22 publications · 5.2K citations

    18

    h-index

  2. Journal of Chemical Theory and Computation

    JCTC · 14 publications · 773 citations

    14

    h-index

  3. Journal of Cataract & Refractive Surgery

    14 publications · 1.4K citations

    13

    h-index

  4. Scientific Reports

    12 publications · 437 citations

    12

    h-index

  5. Perceptual and Motor Skills

    10 publications · 271 citations

    10

    h-index

1–5