If the source matrix is a covariance matrix, then using Cholesky decomposition is efficient. The implementation of QR-Householder matrix inverse presented in this article emphasizes simplicity and ...

Low-rank matrix approximations, such as the truncated singular value decomposition and the rank-revealing QR decomposition, play a central role in data analysis and scientific computing. This work ...

A new orthogonalization technique is presented for computing the $QR$ factorization of a general $n \times p$ matrix of full rank $p (n \geqslant p)$. The method is based on the use of projections to ...