QR decomposition
In linear algebra, a QR decomposition, also known as a QR factorization or QU factorization, is a decomposition of a matrix "A" into a product "A" = "QR" of an orthogonal matrix "Q" and an upper triangular matrix "R". QR decomposition is often used to solve the linear least squares problem and is the basis for a particular eigenvalue algorithm, the QR algorithm.