Hi, I'm attempting to implement a QR factorization with column pivoting so that the returned R matrix has decreasing diagonal elements (that is, $r_{i,i} \leq r_{i-1,i-1}$ for all $i\geq 2$). Mathematically, it would involve finding the matrix $P$ so that $AP=QR$, or $A=QRP^T$. I'm using Gram-Schmidt to compute QR.
One source I found was this: http://www.mathworks.de/matlabcentral/newsreader/view_thread/250632
Quote from the answer: "During the iteration #k, it is easy to show that if we pick among the set of remaining vectors (i.e., not yet included in the span) the vector that has the largest orthogonal component to the current subspace (generated by k first vectors), then the diagonal of R must decrease."
Sounds simple enough, but HOW do I determine which vector of the remaining ones that have the largest orthogonal component to the subspace that's already been found?
Thanks a lot in advance for any help on this matter!
Best regards Hallgeir