I have a matrix $A=QR$, after performing QR decomposition.
Why is it that performing a singular value decomposition on $A$ gives the same answer for $\Sigma$ and $V$ when performing one on the matrix $R$ from the QR decomposition? I'm using the form $A=U\Sigma V^T$ for the SVD
Is it to do with the orthogonality of the matrix $Q$? Regardless, could somebody explain or at least give a hint as to why this happens?