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Moving least squares via orthogonal polynomials [PDF]
, 2009 A method for moving least squares interpolation and differentiation is presented in the framework of orthogonal polynomials on discrete points. This yields a robust and efficient method which can avoid singularities and breakdowns in the moving least ...
Carley, Michael
core +6 more sources
Differentially Private Ordinary Least Squares
The Journal of Privacy and Confidentiality, 2019 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]
Atmospheric Measurement Techniques, 2016 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
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Separations, 2018 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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Least-squares inversion for density-matrix reconstruction [PDF]
, 1997 We propose a method for reconstruction of the density matrix from measurable time-dependent (probability) distributions of physical quantities. The applicability of the method based on least-squares inversion is - compared with other methods - very ...
A. Zucchetti +48 more
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Total Least Squares Registration of 3D Surfaces [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 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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Teaching Least Squares in Matrix Notation
Ratio Mathematica, 2017 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]
International Journal of Data and Network Science, 2023 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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Bayesian least squares deconvolution
, 2015 Aims. To develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods. We consider LSD under the
Petit, P., Ramos, A. Asensio
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Flexible Least Squares Algorithm for Switching Models
Complexity, 2022 The self-organizing model and expectation-maximization method are two traditional identification methods for switching models. They interactively update the parameters and model identities based on offline algorithms. In this paper, we propose a flexible
Yunxia Ni, Lixing Lv, Yuejiang Ji
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