# RMSE between original and predicted values.

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MAT-Magic on 18 Jan 2020
Commented: Star Strider on 20 Jan 2020
Hi,
If I have thousand samples of my signal in a vector form like 1*1000, and I will predict my signal at each iteration that results into 1*1000 also. Then In this case, how will I find the RMSE of my model?
Many Thanks

Star Strider on 18 Jan 2020

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Star Strider on 20 Jan 2020
The RMSE calculation remains the same. You need to take the diferences, square them, accumulate them, take the mean, and the the square root of that.
MAT-Magic on 20 Jan 2020
OK. Thanks alot
Star Strider on 20 Jan 2020
As always, my pleasure!

### More Answers (1)

Image Analyst on 18 Jan 2020
Without any other information, the maximum likelihood prediction for every element would be the mean of the entire signal. But it seems you'd rather have the rms, so you'd have
RMSE = rms(yourVector)
predictionVector = RMSE * ones(length(yourVector));

#### 1 Comment

MAT-Magic on 18 Jan 2020
Thanks for the reply.