How do I test for correlation between digital data series?
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Chris
el 4 de Dic. de 2013
Editada: Wayne King
el 5 de Dic. de 2013
This may be a dumb question. I have two digital data series:
a = [-1 1 -1 -1 -1 1 1 -1 -1 -1 1 1]; b = [1 -1 1 -1 1 1 -1 -1 -1 -1 1 -1];
What's the best way to determine whether they are correlated? Corr? Chi-square? If chi-square, how exactly (there are several functions)?
Thanks
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Wayne King
el 5 de Dic. de 2013
Editada: Wayne King
el 5 de Dic. de 2013
xcorr() is in the Signal Processing Toolbox. You can calculate the cross correlation in the frequency domain and then invert.
a = [-1 1 -1 -1 -1 1 1 -1 -1 -1 1 1];
b = [1 -1 1 -1 1 1 -1 -1 -1 -1 1 -1];
npad = length(a)+length(b)-1;
crosspec = fft(a,npad).*conj(fft(b,npad));
xcr = fftshift(ifft(crosspec));
anorm = norm(a,2)^2;
bnorm = norm(b,2)^2;
xcr = xcr./sqrt(anorm*bnorm);
lags = -length(a)+1:length(a)-1;
stem(lags,xcr,'markerfacecolor',[0 0 1])
Or you can use corrcoef() -- again this is not the best for time series.
R = corrcoef(a,b);
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Wayne King
el 4 de Dic. de 2013
Editada: Wayne King
el 4 de Dic. de 2013
The best way is to compute the cross correlation sequence.
The reason you want to do that is with time series data, you want to account for the fact that the two series may differ only by a shift.
a = [-1 1 -1 -1 -1 1 1 -1 -1 -1 1 1]; b = [1 -1 1 -1 1 1 -1 -1 -1 -1 1 -1];
[c,lags] = xcorr(a,b,'coeff');
stem(lags,c)
Look at some of the "Examples and How Tos" here
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