On growth factors of the modified Gram–Schmidt algorithm
Musheng Wei, Qiaohua Liu · Numerical Linear Algebra with Applications · 2008
Abstract Growth factors play a central role in studying the stability properties and roundoff estimates of matrix factorizations; therefore, they have attracted many numerical analysts to study upper bounds of these growth factors. In this article, we derive several upper bounds of row‐wise growth factors of the modified Gram–Schmidt (MGS) algorithm to solve the least squares (LS) problem and the weighted LS problem. We also extend the analysis to the MGS‐like algorithm to solve the constrained LS problem. Copyright © 2008 John Wiley & Sons, Ltd.