https://doi.org/10.1351/goldbook.10154
Least squares regression that minimizes the sum of squared differences between the known values of dependent variable and values predicted by a linear model.
Notes:
- Assumptions of the model are that error is only in the dependent variable, Normally-distributed, and homoscedastic.
- OLSR is used for calibration and multivariate calibration.