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Linear least squares (mathematics)

Known as: Constrained regression, Constrained linear least squares, Normal equations 
In statistics and mathematics, linear least squares is an approach fitting a mathematical or statistical model to data in cases where the idealized… Expand
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Papers overview

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Highly Cited
2018
Highly Cited
2018
linear algebra. This book covers some of the most important basic ideas from linear algebra, such as linear independence. In a… Expand
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Highly Cited
2012
Highly Cited
2012
Scherrer Equation, L=Kλ/β.cosθ, was developed in 1918, to calculate the nano crystallite size (L) by XRD radiation of wavelength… Expand
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Highly Cited
2007
Highly Cited
2007
For given data ($t_i\ , y_i), i=1, \ldots ,m$ , we consider the least squares fit of nonlinear models of the form F($\underset… Expand
Highly Cited
2003
Highly Cited
2003
Preface 1. Background in linear algebra 2. Discretization of partial differential equations 3. Sparse matrices 4. Basic iterative… Expand
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Highly Cited
2001
Highly Cited
2001
Linear spectral mixture analysis (LSMA) is a widely used technique in remote sensing to estimate abundance fractions of materials… Expand
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Highly Cited
1997
Highly Cited
1997
In this paper a modification of the standard algorithm for non‐negativity‐constrained linear least squares regression is proposed… Expand
Highly Cited
1997
Highly Cited
1997
Analysis and modeling of small-angle scattering data from systems consisting of colloidal particles or polymers in solution are… Expand
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Highly Cited
1993
Highly Cited
1993
  • Y. Saad
  • SIAM J. Sci. Comput.
  • 1993
  • Corpus ID: 12540446
A variant of the GMRES algorithm is presented that allows changes in the preconditioning at every step. There are many possible… Expand
Highly Cited
1944
Highly Cited
1944
The standard method for solving least squares problems which lead to non-linear normal equations depends upon a reduction of the… Expand
Highly Cited
1936
Highly Cited
1936
The mathematical problem of approximating one matrix by another of lower rank is closely related to the fundamental postulate of… Expand