Hello, I am really new at matlab. I am trying to create a sub-function that has an input of two vectors and output the RMSE between the values in the vectors. Anyone can help? I would love to understand step by step. thanks to anybody that can help!!

 Accepted Answer

Star Strider
Star Strider on 5 Mar 2018
Edited: MathWorks Support Team on 2 Mar 2023
UPDATE: Starting in R2022b, you can now calculate Root Mean Square Error using the built in MATLAB function ‘rmse’:
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‘RMSE’ of course means ‘root mean squared error’, or the square root of the mean of the squared error.
The simplest code for this is then:
V1 = rand(10,1);
V2 = rand(10,1);
RMSE = sqrt(mean((V1-V2).^2));
where the error is (V1-V2), and ‘.^2’ denotes element-wise squaring of the error (the difference between ‘V1’ and ‘V2’). The rest of the expression takes the mean of the squared differences, and sqrt takes the square root, completing the definition.
See: Array vs. Matrix Operations (link) and Vectorization (link) for more information.

12 Comments

thank you so much!!!
As always, my pleasure!
what is v1 and v2
Anything you want them to be!
MAT-Magic
MAT-Magic on 18 Jan 2020
Edited: MAT-Magic on 18 Jan 2020
@ Dear Star Strider can we use the below formula for V1 and V2?
difference = single(1) - single(2);
squaredError = difference .^ 2;
meanSquaredError = sum(squaredError(:)) / numel(signal(1));
rmsError = sqrt(meanSquaredError);
Thanks
That appears to be the correct way to calculate RMSE.
Thanks. I edited the question and removed the mistakes.
My pleasure.
I assume ‘single(1)’ and ‘single(2)’ are actually equal-length vectors.
There is an rms() function that you can use. It's been in the Signal Processing Toolbox since R2012a.
@Star Yes, it's right.
@Image Thanks for the reply.
@Image Analyst,
I don't think RMSE and RMS are the same; I'm currently fining that out...
Yes and No. Actually, RMSE=rms(E), since E(rror) is the difference. In the example above: RMSE=rms(V1-V2)

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More Answers (1)

To learn Matlab, you can use a guide like this one.
There are two main ways of doing this: an anonymous function and a 'normal' function.
%anonymous function:
calculate_RMSE=@(a,b) sqrt(mean((a(:)-b(:)).^2));
%normal function (save this in calc_RMSE.m)
function rmse=calc_RMSE(a,b)
rmse=sqrt(mean((a(:)-b(:)).^2));
The two function can be used in the exact same way. The second option provides more options for checking if the input is correct.

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