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Least squares

Known as: Least squares method, Least-squares fit, LS 
The method of least squares is a standard approach in regression analysis to the approximate solution of overdetermined systems, i.e., sets of… Expand
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Highly Cited
2016
Highly Cited
2016
Least-squares means are predictions from a linear model, or averages thereof. They are useful in the analysis of experimental… Expand
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Highly Cited
2007
Highly Cited
2007
Let A be a real m×n matrix with m≧n. It is well known (cf. [4]) that $$A = U\sum {V^T}$$ (1) where $${U^T}U = {V^T}V… Expand
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Highly Cited
2003
Highly Cited
2003
We propose a new approach to reinforcement learning for control problems which combines value-function approximation with linear… Expand
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Highly Cited
1995
Highly Cited
1995
Since the lm function provides a lot of features it is rather complicated. So we are going to instead use the function lsfit as a… Expand
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Highly Cited
1985
Highly Cited
1985
The method of weighted least squares is shown to be an appropriate way of fitting variogram models. The weighting scheme… Expand
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Highly Cited
1985
Highly Cited
1985
The Adaptive Least Squares Correlation is a very potent and flexible technique for all kinds of data matching problems. Here its… Expand
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Highly Cited
1982
Highly Cited
1982
  • S. P. Lloyd
  • IEEE Trans. Inf. Theory
  • 1982
  • Corpus ID: 10833328
It has long been realized that in pulse-code modulation (PCM), with a given ensemble of signals to handle, the quantum values… Expand
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Highly Cited
1982
Highly Cited
1982
An iterative method is given for solving Ax ~ffi b and minU Ax b 112, where the matrix A is large and sparse. The method is based… Expand
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Highly Cited
1976
Highly Cited
1976
The statistical properties of least-squares frequency analysis of unequally spaced data are examined. It is shown that, in the… Expand
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Highly Cited
1966
Highly Cited
1966
A detailed discussion of the calculation of the "best straight line" by the method of least squares is given. The most general… Expand
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