calculating rmse between observations and estimates of different size

I would like to calculate rmse between observations and estimates of different size. This are two timeseries, one 84084x1 and the second is 315360x1.

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Your data sets (data and estimate) have different sizes. Do you have NaN's in your estimates or are you taking multiple estimates/observations?
You might want to equalize the size of the dataset (by removing the unwanted observations) and then finding the rmse
rmse=sqrt(sum((data(:)-estimate(:)).^2)/numel(data));

3 Commenti

The are gaps in the observation. Is there a way to fill those gaps in a time step with a zero or interpolation?
You could try interp1 (nearest neighbor interpolation) or something similar http://www.mathworks.com/help/matlab/ref/interp1.html
I just realized that you have a time series and if you have the finance toolbox you can use the fillts command http://www.mathworks.com/help/finance/fillts.html

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Più risposte (1)

You can padd the small vector with zero or Interpolate as mentioned by @Thomas :
% Given your vectors r1 r2
r1=randn(315360,1);
r2=randn(84084,1);
N1=length(r1);
N2=length(r2);
Ratio=floor(N1/N2);
r22=interp(r2,Ratio);
Diff=N1-length(r22);
r22=[r22;zeros(Diff,1)];
plot(r1), hold on, plot(r22,'r'),
RMSE=sqrt(mean(((r22-r1).^2)))
You can also use the functions downsample or upsample

2 Commenti

Hi Youssef,
I tried your code but it gives me error:
Error using horzcat Dimensions of matrices being concatenated are not consistent.
Error in usgs (line 107) r22=[r22 zeros(1,Diff)];
Thanks though. It has potential
Sergio, transpose vectors r1=r1'; r2=r2' or try again the edited code .

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