Statistical Yield Modeling

Statistical Yield Modeling is a computational framework that belongs to the class of yield estimation methods, distinguished by its use of statistical inference and probabilistic models to quantify and predict agricultural or industrial output based on observed input variables and historical data.

223

Publications

10.9K

Citations

695

Authors

329

Institutions

Publications per year

2017–2026

60

Authors

695

  1. OA
    Octavio A. Ramírez

    Texas Tech University, United States

    5 publications · 315 citations

    5

    h-index

  2. CS
    C.H. Stapper

    IBM (United States), United States

    4 publications · 622 citations

    4

    h-index

  3. JB
    J.W. Bandler

    McMaster University, Canada

    3 publications · 70 citations

    3

    h-index

  4. PC
    P.K. Chatterjee

    Texas Instruments (United States), United States

    3 publications · 224 citations

    3

    h-index

  5. DM
    David Makowski

    AgroParisTech, France

    3 publications · 128 citations

    3

    h-index

1–5 of 695

Venues

  1. American Journal of Agricultural Economics

    11 publications · 937 citations

    11

    h-index

  2. 10

    h-index

  3. Field Crops Research

    7 publications · 488 citations

    7

    h-index

  4. 6

    h-index

  5. Remote Sensing

    6 publications · 417 citations

    6

    h-index

1–5