fitgoodness

[r, R2, RMSE, MAE, SI, NSE, d, Bias, NMBias, RE] = fitgoodness(x, y, dispout)

Description

Calculate goodness of fit parameters

Inputs

x

Dataset with true (exact or expected) values, such as theoretical values

y

Dataset that needs to be evaluated, such as model results or estimated values

Accuracy of y dataset is evaluated against x dataset

dispout=’no’;

Define to display outputs or not (‘yes’: display, ‘no’: not display)

Outputs

r

Pearson correlation coefficient

R2

Coefficient of determination

RMSE

Root mean square error

MAE

Mean absolute error

SI

Scatter index

NSE

Nash Sutcliffe efficiency coefficient

d

Index of agreement

Bias

Bias

NMBias

Normalized mean bias

RE

Relative error

Examples

x(:,1)=(-0.1+(0.1-(-0.1))).*randn(1024*2,1);
y(:,1)=x+(-0.01+(0.01-(-0.01))).*randn(1024*2,1);
[r,R2,RMSE,MAE,SI,NSE,d,Bias,NMBias,RE]=fitgoodness(x,y,'yes');

x=[1;2;3;4;5;6;7;8;9;10];
y=[1.1;1.98;3.3;4.2;4.8;5.95;7.5;7.7;8.99;10.5];
[r,R2,RMSE,MAE,SI,NSE,d,Bias,NMBias,RE]=fitgoodness(x,y,'yes');

References