27 December, 2020 (Jung, bg, FLUXCOM carbon) Gervasio Piรฑeiro, Susana Perelman, Juan P. Guerschman, Josรฉ M. Paruelo, How to evaluate models: Observed vs. predicted or predicted vs. observed?, Ecological Modelling, Volume 216, Issues 3โ4, 2008, Pages 316-322, ISSN 0304-3800, https://doi.org/10.1016/j.ecolmodel.2008.05.006.
Prediction (x-axis) vs. Observation (y-axis) Martin added a comment to my proposal. He said that I should put prediction on the x-axis, referring to a paper:
I have just look over the conclusion of the paper.
Robust linear regression Sujan recommended me to use the robust regression models (RLM) instead of the standard OLS (ordinary least squares). What are the differences?
Robust: less affected by outliers A drawback of OLS is that the resulted regression line can be significantly altered by some outliers. As the OLS try to find a best line of the minimum SS, the optimum would likely to have more focus on outliers which have large SS.
