MATLAB: Cov computation in Matlab

cov

If the definition of covariance is (x-mean(x))'*(x-mean(x)), why cov(x) does not return the same result? Thank you.

Best Answer

The 'cov' function normalizes by dividing by N-1 where N is the number of observations, which in this case is the number of rows in your matrix x.

Related Solutions

MATLAB: Can the XCOV function return a result that is both unbiased and normalized

The ability to create estimates of the cross-covariance function that are both unbiased and normalized is not available in the Signal Processing Toolbox.

To work around this issue, create unbiased estimates and normalize by the zero lag term manually, as in the following example:

ww = randn(1000,1);
N = 10;
[cov_ww,lags] = xcov(ww,N,'unbiased');
cov_ww = cov_ww / cov_ww(N+1);
stem(lags,cov_ww)

MATLAB: Estimating the parameter of an equation

Um, don't use fminsearch? In fact, I'm not sure why you would want to do it that way.

d = 17;
n = 10000;
kk=randn(n,1);
u=randn(n-1,1);
kk(2:end)=kk(1:end-1)+u*d;

Now, estimate d. For this simple problem, diff and std are about all you really need.

dhat = std(diff(kk))/sqrt(2)
dhat =
          17.1535533234171

Best Answer

Related Solutions

MATLAB: Can the XCOV function return a result that is both unbiased and normalized

MATLAB: Estimating the parameter of an equation

Related Question