On the nonuniqueness of low-rank matrix factors

A common task in statistics is to approximate a large data matrix by using a low-rank approximation. Low-rank approximations are used for reducing the dimension of a problem (for example, in principal component analysis), for image analysis via the singular value decomposition (SVD), and for decomposing large matrices that are …