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Least-Squares Analysis

Known as: Analyses, Least-Squares, Least Squares, Least Square 
A principle of estimation in which the estimates of a set of parameters in a statistical model are those quantities minimizing the sum of squared… Expand
National Institutes of Health

Papers overview

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Highly Cited
2016
Highly Cited
2016
In confirmatory factor analysis (CFA), the use of maximum likelihood (ML) assumes that the observed indicators follow a… Expand
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Highly Cited
2012
Highly Cited
2012
Due to the simplicity of their implementations, least square support vector machine (LS-SVM) and proximal support vector machine… Expand
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Highly Cited
2010
Highly Cited
2010
Partial least squares regression has been an alternative to ordinary least squares for handling multicollinearity in several… Expand
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Highly Cited
2001
Highly Cited
2001
Recent advances in molecular genetic techniques will make dense marker maps available and genotyping many individuals for these… Expand
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Highly Cited
1998
Highly Cited
1998
This paper presents a numerically stable non-iterative algorithm for fitting an ellipse to a set of data points. The approach is… Expand
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Highly Cited
1996
Highly Cited
1996
This paper introduces a new tool for functional neuroimage analysis: partial least squares (PLS). It is unique as a multivariate… Expand
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Highly Cited
1996
Highly Cited
1996
The application of the ‘‘model trust region’’ modification of the instrumentation. Two of the most important advances inLevenberg… Expand
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Highly Cited
1972
Highly Cited
1972
The linearity of the detection system including the attenuator will directly affect the accuracy of 0 and should be considered… Expand
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Highly Cited
1950
Highly Cited
1950
A great deal of use has undoubtedly been made of least squares regression methods in circumstances in which they are known to be… Expand
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Highly Cited
1950
Highly Cited
1950
 
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