Statistical Loss Modeling

Statistical Loss Modeling is a quantitative analytical framework that employs statistical methods to estimate and predict crop yield reductions due to biotic, abiotic, or anthropogenic factors by differentiating patterns of observed loss data from expected production baselines.

58

Publications

3.7K

Citations

169

Authors

96

Institutions

Publications per year

2017–2026

11

Authors

169

  1. AB
    Anouar Belahcen

    Aalto University, Finland

    4 publications · 161 citations

    4

    h-index

  2. SL
    Sébastien Laurent

    UCLouvain, Belgium

    3 publications · 196 citations

    3

    h-index

  3. JV
    Jeroen V.K. Rombouts

    UCLouvain, Belgium

    3 publications · 196 citations

    3

    h-index

  4. FM
    Floran Martin

    Aalto University, Finland

    2 publications · 108 citations

    2

    h-index

  5. JA
    Jose A. Lopez

    Federal Reserve Bank of San Francisco, United States

    2 publications · 44 citations

    2

    h-index

1–5 of 169

Venues

  1. IEEE Transactions on Magnetics

    4 publications · 426 citations

    4

    h-index

  2. Crop Protection

    3 publications · 57 citations

    3

    h-index

  3. Journal of Nuclear Science and Technology

    JNST · 2 publications · 30 citations

    2

    h-index

  4. SSRN Electronic Journal

    Repository · 2 publications · 62 citations

    2

    h-index

  5. Quantitative Finance

    1 publications · 15 citations

    1

    h-index

1–5