The weighting method for solving a least squares problem with linear equality constraints multiplies the constraints by a large number and appends them to the top of the least squares problem, which is then solved by standard techniques. In this paper we give a new analysis of the method, based on the QR decomposition, that exhibits many features of the algorithm. In particular it suggests a natural criterion for chosing the weighting factor. This report is available by anonymous ftp from thales.cs.umd.edu in the directory pub/reports or through the web at http://www.cs.umd.edu/ stewart/. y Department of Computer Science and Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20742. This work was supported...
The purpose of this note is to re-introduce the generalized QR factorization with or without pivotin...
The solution of nearly square overdetermined linear systems is studied. The sparse QR technique is c...
We address the problem of solving linear least-squares problems min——Ax−b—— when A is a sparse m-by-...
Abstract In this article, we present a QR updating procedure as a solution approach for linear least...
Abstract. It is well known that the solution of the equality constrained least squares (LSE) problem...
We consider a repeated QR updating algorithm for the solution of equality constrained linear least s...
It is well known that the solution of the equality constrained least squares (LSE) problem min Bx=d ...
. In 1980, Han [6] described a finitely terminating algorithm for solving a system Ax b of linear ...
This is an extension of the work in SAND--80-0655 to the weighted linear least squares problem. Give...
The null space method is a standard method for solving the linear least squares problem subject to e...
AbstractIn this paper, some new properties of the equality constrained and weighted least squares pr...
Consider a full-rank weighted least-squares problem in which the weight matrix is highly ill-conditi...
In this thesis, we consider two closely related problems. The first is a full-rank weighted least-s...
A backward error analysis of the direct elimination method for linear equality constrained least squ...
This paper aims to investigate some theoretical characteristics of the solu-tion of constrained and ...
The purpose of this note is to re-introduce the generalized QR factorization with or without pivotin...
The solution of nearly square overdetermined linear systems is studied. The sparse QR technique is c...
We address the problem of solving linear least-squares problems min——Ax−b—— when A is a sparse m-by-...
Abstract In this article, we present a QR updating procedure as a solution approach for linear least...
Abstract. It is well known that the solution of the equality constrained least squares (LSE) problem...
We consider a repeated QR updating algorithm for the solution of equality constrained linear least s...
It is well known that the solution of the equality constrained least squares (LSE) problem min Bx=d ...
. In 1980, Han [6] described a finitely terminating algorithm for solving a system Ax b of linear ...
This is an extension of the work in SAND--80-0655 to the weighted linear least squares problem. Give...
The null space method is a standard method for solving the linear least squares problem subject to e...
AbstractIn this paper, some new properties of the equality constrained and weighted least squares pr...
Consider a full-rank weighted least-squares problem in which the weight matrix is highly ill-conditi...
In this thesis, we consider two closely related problems. The first is a full-rank weighted least-s...
A backward error analysis of the direct elimination method for linear equality constrained least squ...
This paper aims to investigate some theoretical characteristics of the solu-tion of constrained and ...
The purpose of this note is to re-introduce the generalized QR factorization with or without pivotin...
The solution of nearly square overdetermined linear systems is studied. The sparse QR technique is c...
We address the problem of solving linear least-squares problems min——Ax−b—— when A is a sparse m-by-...