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Journal ArticleDOI

Linear least squares solutions by householder transformations

Peter A. Businger, +1 more
- 01 Jun 1965 - 
- Vol. 7, Iss: 3, pp 269-276
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TLDR
In this paper, the euclidean norm is unitarily invariant and a vector x is determined such that x is parallel b-Ax parallel = \parallel c - QAx parallel where c denotes the first n components of c.
Abstract
Let A be a given m×n real matrix with m≧n and of rank n and b a given vector. We wish to determine a vector x such that $$\parallel b - A\hat x\parallel = \min .$$ where ∥ … ∥ indicates the euclidean norm. Since the euclidean norm is unitarily invariant $$\parallel b - Ax\parallel = \parallel c - QAx\parallel $$ where c=Q b and Q T Q = I. We choose Q so that $$QA = R = {\left( {_{\dddot 0}^{\tilde R}} \right)_{\} (m - n) \times n}}$$ (1) and R is an upper triangular matrix. Clearly, $$\hat x = {\tilde R^{ - 1}}\tilde c$$ where c denotes the first n components of c.

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Citations
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Approximate Generalized Inverse Preconditioning Methods for Least Squares Problems

Xiaoke Cui
TL;DR: Two different approaches for how to construct the approximate generalized inverses of the coefficient matrices of the least squares problems are proposed: one is based on the Minimal Residual method with the steepest descend direction, and the other isbased on the Greville’s Method which is an old method developed for computing the generalized inverse based onThe rank-one update.
Journal ArticleDOI

A sequential quadratic programming algorithm utilizing qr matrix factorization

TL;DR: Numerical results show that SQR as devised in this paper is the best method as far as robustness and speed of convergence are concerned in solving general constrained optimization problems.

Numerical methods for estimating linear econometric models

Paolo Foschi
TL;DR: In this article, the authors investigated and developed efficient numerical and computational methods for solving large scale Seemingly Unrelated Regressions (SUR) models, which substantially reduce the computational burden of the estimation procedures.
Journal ArticleDOI

A survey of published programs for best approximation

TL;DR: In this paper, a list and discussion of published programs for best approximations of functions by linear and nonlinear families in all standard forms is presented.==================\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/)|

Effcient magnetometer sensor array selection for signal reconstruction and brain source localization

TL;DR: It is suggested that principled methods for sensor selection can improve MEG capabilities and potentially add cost savings for monitoring brain-wide activity.
References
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Journal ArticleDOI

Unitary Triangularization of a Nonsymmetric Matrix

TL;DR: This note points out that the same result can be obtained with fewer arithmetic operations, and, in particular, for inverting a square matrix of order N, at most 2(N-1) square roots are required.