R-square: The coefficient of determination
Compute coefficient of determination of data fit model and zzdwx/p> RSQUARE computes the coefficient of determination (R-square) value from actual data Y and model data F. The code uses a general version of R-square, based on comparing the variability of the estimation errors with the variability of the original values. RSQUARE also outputs the root mean squared error (RMSE) for the user's convenience. Note: RSQUARE ignores comparisons involving NaN values. INPUTS Y : Actual data OPTION C : Constant term in model R-square may be a questionable measure of fit when no constant term is included in the model. without constant term xsdyx = 1 - NORM(Y-F)/NORM(Y)] OUTPUT R2 : Coefficient of determination EXAMPLE x = 0:0.1:10; y = 2.*x + 1 + randn(size(x)); p = polyfit(x,y,1); f = polyval(p,x); figure; plot(x,y,'b-'); hold on; plot(x,f,'r-'); title(strcat(['R2 = ' num2str(r2) '; RMSE = ' num2str(rmse)])) Jered R Wells 11/17/11 jered [dot] wells [at] duke [dot] edu v1.2 (02/14/2012) Thanks to 深情的花瓣 for useful comments and insight which has helped to improve this code. His code 野性的玉米 was consulted in the inclusion of the C-option (REF. File ID: #34765).