[EDIT: 20110610 00:17 CDT - reformat - WDR]
So i was looking online how to check the RMSE of a line. found many option, but I am stumble about something,
there is the formula to create the RMSE: http://en.wikipedia.org/wiki/Root_mean_square_deviation
Dates - a Vector
Scores - a Vector
is this formula is the same as RMSE=sqrt(sum(Dates-Scores).^2)./Dates
or did I messed up with something?
Yes, it is different. The Root Mean Squared Error is exactly what it says.
(y - yhat) % Errors (y - yhat).^2 % Squared Error mean((y - yhat).^2) % Mean Squared Error RMSE = sqrt(mean((y - yhat).^2)); % Root Mean Squared Error
What you have written is different, in that you have divided by dates, effectively normalizing the result. Also, there is no mean, only a sum. The difference is that a mean divides by the number of elements. It is an average.
Thus, you have written what could be described as a "normalized sum of the squared errors", but it is NOT an RMSE. Perhaps a Normalized SSE.
If you have the Image Processing Toolbox, you can use immse():
rmse = sqrt(immse(scores, dates));
Root mean square error is difference of squares of output an input. Let say x is a 1xN input and y is a 1xN output. square error is like (y(i) - x(i))^2. Mean square error is 1/N(square error). and its obvious RMSE=sqrt(MSE).
ur code is right. But how r dates and scores related?
How to apply RMSE formula to measure differences between filters to remove noisy pictures such a median , mean and weiner fiters ? how can i get the result or how to apply it . Rgards .