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Stdlib has corr and cov functions that compute the correlation and covariance matrices of the columns of an array. Computing the correlation matrix of the columns of array A, assuming that the elements of each column have been shifted by the column mean, involves calculating
matmul(transpose(A),A)
Could this be added as a function? If this can be computed efficiently, the programmer can calculate the correlation matrix using computed or a priori means and variances, as I described in Give stats functions optional mean arguments?
BLAS does have dgemm to multiply matrices, either of which may be transposed, but does it optimize the special but common case that the two matrices are the same?
The text was updated successfully, but these errors were encountered:
Stdlib has corr and cov functions that compute the correlation and covariance matrices of the columns of an array. Computing the correlation matrix of the columns of array A, assuming that the elements of each column have been shifted by the column mean, involves calculating
matmul(transpose(A),A)
Could this be added as a function? If this can be computed efficiently, the programmer can calculate the correlation matrix using computed or a priori means and variances, as I described in Give stats functions optional mean arguments?
BLAS does have dgemm to multiply matrices, either of which may be transposed, but does it optimize the special but common case that the two matrices are the same?
The text was updated successfully, but these errors were encountered: