Regression-based Calibration

Regression-Based Calibration is a calibration method that employs regression analysis to model the relationship between sensor measurements and reference values, thereby enabling the correction of systematic errors in yield monitor data through statistical estimation.

117

Publications

6.9K

Citations

365

Authors

191

Institutions

Publications per year

2017–2026

31

Authors

365

  1. DS
    Donna Spiegelman

    Harvard University, United States

    3 publications · 68 citations

    3

    h-index

  2. SW
    Sally W. Thurston

    University of Rochester, United States

    2 publications · 44 citations

    2

    h-index

  3. FA
    Fred A. van Eeuwijk

    Wageningen University & Research, Netherlands

    2 publications · 37 citations

    2

    h-index

  4. RG
    Richard G. Krutchkoff

    Virginia Tech, United States

    2 publications · 350 citations

    2

    h-index

  5. CC
    Chi-Lun Cheng

    Institute of Statistical Science, Academia Sinica, Taiwan

    2 publications · 26 citations

    2

    h-index

1–5 of 365

Venues

  1. Applied Spectroscopy

    6 publications · 157 citations

    6

    h-index

  2. Journal of Near Infrared Spectroscopy

    JNIRS · 5 publications · 114 citations

    5

    h-index

  3. Technometrics

    5 publications · 1.5K citations

    5

    h-index

  4. 5

    h-index

  5. Sensors

    4 publications · 90 citations

    4

    h-index

1–5