Description Usage Arguments Details Author(s) References
Common interface for metrics commonly for assessing quality of hydrologic models, statistical or otherwise.
1 2 3 4 5 | excelR2(x.obs, x.model)
rmse(x.obs, x.model)
rmse(residuals)
nash.sutcliffe(x.obs, x.model)
nash.sutcliffe(x.obs, x.model, x.alt)
|
x.obs |
- observed values |
x.model |
- modeled values |
x.alt |
- alternate model for comparison (Nash Sutcliffe only, defaults to mean of observed) |
excelR2
returns the R^2 as reported by Excel's curve fits. It is provided as people are comfortable with it, but is a terrible measure of model accuracy. See the references below.
rmse
returns the root mean square error. With one parameter assumes x.obs is residuals, with two, computes residuals between x.obs and x.model
nash.sutcliffe
returns the Nash-Sutcliffe model coefficent, greater than 0 if 'x.model' is a better fit than x.alt, 1 if a perfect fit, and between 0 and -infinity if a worse fit than x.alt.
Evan Heisman
Hopper, T. (2014), Can We do Better than R-squared? http://www.r-bloggers.com/can-we-do-better-than-r-squared/ retrieved 16 May 2014
Nash, J. E. and J. V. Sutcliffe (1970), River flow forecasting through conceptual models part I - A discussion of principles, Journal of Hydrology, 10 (3), 282-290.
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