Abstract. We show that the well-known least squares (LS) solution of an overdetermined system of linear equations is a convex combination of all the non-trivial solutions weighed by the squares of the corre-sponding denominator determinants of the Cramer’s rule. This Least Squares Decomposition (LSD) gives an alternate statistical interpretation of least squares, as well as another geometric meaning. Furthermore, when the singular values of the matrix of the overdetermined system are not small, the LSD may be able to provide flexible solutions. As an illustration, we apply the LSD to interpret the LS-solution in the problem of source localization. Key Words and Phrases: least squares decomposition, least squares solution, overdetermined sys...
SIGLEAvailable from British Library Document Supply Centre- DSC:5644.91(RSRE-M--3864) / BLDSC - Brit...
The Method of Least Squares is a procedure to determine the best fit line to data; the proof uses si...
The theoretical aspect of least squares. This article contains a slightly modified presentation of t...
Abstract. We show that the well-known least squares (LS) solution of an overdetermined system of lin...
AbstractWe derive an explicit determinantal formula for the least squares solution of an overdetermi...
In this paper, we address the accuracy of the results for the overdetermined full rank linear least ...
In this paper, we prove a new identity for the least-square solution of an over-determined set of li...
In this paper, we address the accuracy of the results for the overdetermined full rank linear least ...
Four methods for the least squares solution of overdetermined systems of linear equations are compar...
AbstractThis article surveys the history, development, and applications of least squares, including ...
The main goal of this work is to present the least squares method to solve overdetermined linear sys...
Least squares method theory and application to curve fitting, data smoothing, and solution of overde...
AbstractAn algorithm for computing solutions of overdetermined systems of linear equations in n real...
The least-squares method was firmly established as a scientific approach by Gauss, Legendre and Lapl...
AbstractAn algorithm previously introduced by the author for finding a feasible point of a system of...
SIGLEAvailable from British Library Document Supply Centre- DSC:5644.91(RSRE-M--3864) / BLDSC - Brit...
The Method of Least Squares is a procedure to determine the best fit line to data; the proof uses si...
The theoretical aspect of least squares. This article contains a slightly modified presentation of t...
Abstract. We show that the well-known least squares (LS) solution of an overdetermined system of lin...
AbstractWe derive an explicit determinantal formula for the least squares solution of an overdetermi...
In this paper, we address the accuracy of the results for the overdetermined full rank linear least ...
In this paper, we prove a new identity for the least-square solution of an over-determined set of li...
In this paper, we address the accuracy of the results for the overdetermined full rank linear least ...
Four methods for the least squares solution of overdetermined systems of linear equations are compar...
AbstractThis article surveys the history, development, and applications of least squares, including ...
The main goal of this work is to present the least squares method to solve overdetermined linear sys...
Least squares method theory and application to curve fitting, data smoothing, and solution of overde...
AbstractAn algorithm for computing solutions of overdetermined systems of linear equations in n real...
The least-squares method was firmly established as a scientific approach by Gauss, Legendre and Lapl...
AbstractAn algorithm previously introduced by the author for finding a feasible point of a system of...
SIGLEAvailable from British Library Document Supply Centre- DSC:5644.91(RSRE-M--3864) / BLDSC - Brit...
The Method of Least Squares is a procedure to determine the best fit line to data; the proof uses si...
The theoretical aspect of least squares. This article contains a slightly modified presentation of t...