Goodness-of-Fit Functions for Comparison of Simulated and Observed Hydrological Time Series
Kling-Gupta Efficiency
Kling-Gupta Efficiency with knowable-moments
Kling-Gupta Efficiency for low values
Non-parametric version of the Kling-Gupta Efficiency
Mean Absolute Error
Modified Index of Agreement
Mean Error
Modified Nash-Sutcliffe efficiency
Mean Squared Error
Normalized Root Mean Square Error
Nash-Sutcliffe Efficiency
Percent Bias
Percent Bias in the Slope of the Midsegment of the Flow Duration Curve
P-factor
Plotting 2 Time Series
Plot a ts with observed values and two confidence bounds
Index of Agreement
Refined Index of Agreement
Graphical Goodness of Fit
Numerical Goodness-of-fit measures
High-flows bias
Internal hydroGOF objects
Goodness-of-fit (GoF) functions for numerical and graphical comparison...
br2
Coefficient of persistence
Annual Peak Flow Bias
Adds uncertainty bounds to an existing plot.
Coefficient of determination
Relative Index of Agreement
R-factor
Root Mean Square Error
Relative Nash-Sutcliffe efficiency
Pearson correlation coefficient
Ratio of Standard Deviations
Spearman's rank correlation coefficient
Ratio of RMSE to the standard deviation of the observations
Split Kling-Gupta Efficiency
Sum of the Squared Residuals
Unbiased Root Mean Square Error
Valid Indexes
Volumetric Efficiency
Weighted Nash-Sutcliffe efficiency
Weighted seasonal Nash-Sutcliffe Efficiency
S3 functions implementing both statistical and graphical goodness-of-fit measures between observed and simulated values, mainly oriented to be used during the calibration, validation, and application of hydrological models. Missing values in observed and/or simulated values can be removed before computations. Comments / questions / collaboration of any kind are very welcomed.