GOF

Source: R/coefficients.R

Good of fitting

GOF(Y_obs, Y_sim, w, include.r = TRUE, include.cv = FALSE)

Arguments

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.

Value

  • 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

References

Zhang Xiaoyang (2015), http://dx.doi.org/10.1016/j.rse.2014.10.012

Examples

Y_obs = rnorm(100)
Y_sim = Y_obs + rnorm(100)/4
GOF(Y_obs, Y_sim)
#>         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