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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