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calcCovarMarix works great for calculating the auto-covariance matrix of a given sample set.

Now, how does one calculate the cross-covariance of 2 sample sets, which possibly have a different amount of samples?

calcCovarMarix works great for calculating the auto-covariance matrix of a given sample set.

Now, how does one calculate the cross-covariance of 2 sample sets, which possibly have a different amount of samples?

Mat A = [[1, 2],
         [2, 3]]

Mat B = [[3, 4],
         [4, 5],
         [5, 6]]

calcCovarMarix works great for calculating the auto-covariance matrix of a given sample set.

Now, how does one calculate the cross-covariance of 2 sample sets, which possibly have a different amount of samples?

Example: every row of a matrix is a sample. Samples are random vectors:

Mat A = [[1, 2],
         [2, 3]]

Mat B = [[3, 4],
         [4, 5],
         [5, 6]]

In MATLAB one can simply do cov(A, B). How would one do it in C++ OpenCV?

calcCovarMarix works great for calculating the auto-covariance matrix of a given sample set.

Now, how does one calculate the cross-covariance of 2 sample sets, which possibly have a different amount of samples?

Example: every row of a matrix is a sample. Samples are random vectors:

Mat A = [[1, 2],
         [2, 3]]

Mat B = [[3, 4],
         [4, 5],
         [5, 6]]

In MATLAB one can simply do cov(A, B). How would one do it in C++ OpenCV?

calcCovarMarix works great for calculating the auto-covariance matrix of a given sample set.

Now, how does one calculate the cross-covariance of 2 sample sets, which possibly have a different amount of samples?sets?

Example: every row of a matrix is a sample. Samples are random vectors:

Mat A = [[1, 2],
         [2, 3]]

Mat B = [[3, 4],
4, 5],
         [4, 5],
         [5, 5, 6]]

In MATLAB one can simply do cov(A, B). How would one do it in C++ OpenCV?

calcCovarMarix works great for calculating the auto-covariance matrix of a given sample set.

Now, how does one calculate the cross-covariance of 2 sample sets?

Example: every row of a matrix is a sample. Samples are random vectors:vectors with possibly differing amount of variables:

Mat A = [[1, 2],
         [2, 3]]

Mat B = [[3, 4, 5],
         [4, 5, 6]]

In MATLAB one can simply do cov(A, B). How would one do it in C++ OpenCV?