Results 21 to 30 of about 556,024 (263)
GALS – Gradient Analysis by Least Squares [PDF]
We present a method, GALS (Gradient Analysis by Least Squares) for estimating the gradient of a physical field from multi-spacecraft observations.
M. Hamrin +4 more
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Differentially Private Ordinary Least Squares
Linear regression is one of the most prevalent techniques in machine learning; however, it is also common to use linear regression for its explanatory capabilities rather than label prediction.
Or Sheffet
doaj +1 more source
Non-parametric and least squares Langley plot methods [PDF]
Langley plots are used to calibrate sun radiometers primarily for the measurement of the aerosol component of the atmosphere that attenuates (scatters and absorbs) incoming direct solar radiation.
P. W. Kiedron, J. J. Michalsky
doaj +1 more source
It is necessary to determine the limit of detection when validating any analytical method. For methods with a linear response, a simple and low labor-consuming procedure is to use the linear regression parameters obtained in the calibration to estimate ...
Juan M. Sanchez
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Total Least Squares Registration of 3D Surfaces [PDF]
Co-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of coregistration is to merge the overlapping point clouds by estimating the spatial transformation parameters.
U. Aydar +3 more
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On the Least Median Square Problem [PDF]
We consider the exact and approximate computational complexity of the multivariate least median-of-squares (LMS) linear regression estimator. The LMS estimator is among the most widely used robust linear statistical estimators. Given a set of n points in ${\Bbb R}^d$ and a parameter k, the problem is equivalent to computing the narrowest slab bounded ...
Jeff Erickson 0001 +2 more
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Teaching Least Squares in Matrix Notation
Material for teaching least squares at the undergraduate level in matrix notation is reported. The weighted least squares equations are first derived in matrix form; equivalence with the standard results obtained by standard algebra are then given for ...
Guglielmo Monaco, Aniello Fedullo
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The performance of unweighted least squares and regularized unweighted least squares in estimating factor loadings in structural equation modeling [PDF]
In a confirmatory study, researchers are expected to employ the covariance-based structural equation modeling (CB-SEM). One of the key presumptions when utilizing CB-SEM is that the data is multivariate normal.
Nurul Raudhah Zulkifli +2 more
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Convergence of a Distributed Least Squares
8 pages, published in IEEE Transactions on Automatic ...
Siyu Xie, Yaqi Zhang, Lei Guo 0001
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Least Squares for Practitioners [PDF]
In experimental science and engineering, least squares are ubiquitous in analysis and digital data processing applications. Minimizing sums of squares of some quantities can be interpreted in very different ways and confusion can arise in practice, especially concerning the optimality and reliability of the results.
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