Good of fitting
GOF(Y_obs, Y_sim, w, include.r = TRUE, include.cv = FALSE)
Y_obs | Numeric vector, observations |
---|---|
Y_sim | Numeric vector, corresponding simulated values |
w | Numeric vector, weights of every points. If w included, when calculating mean, Bias, MAE, RMSE and NSE, w will be taken into considered. |
include.r | If true, r and R2 will be included. |
include.cv | If true, cv will be included. |
RMSE
root mean square error
NSE
NASH coefficient
MAE
mean absolute error
AI
Agreement index (only good points (w == 1)) participate to
calculate. See details in Zhang et al., (2015).
Bias
bias
Bias_perc
bias percentage
n_sim
number of valid obs
cv
Coefficient of variation
R2
correlation of determination
R
pearson correlation
pvalue
pvalue of R
Zhang Xiaoyang (2015), http://dx.doi.org/10.1016/j.rse.2014.10.012
#> RMSE NSE MAE AI Bias Bias_perc #> 2.539274e-01 9.410265e-01 2.110004e-01 9.854096e-01 2.871420e-02 4.056297e-01 #> n_sim R2 R pvalue #> 1.000000e+02 9.443434e-01 9.717733e-01 2.803541e-63