Results 11 to 20 of about 578,053 (288)

Condition numbers of the minimum norm least squares solution for the least squares problem involving Kronecker products

open access: yesAIMS Mathematics, 2021
In this paper, the upper bounds for two kinds of normiwse condition numbers are derived for $ \min\limits_{x}\|(A\otimes B)x-b\|_2 $ when the coefficient matrix is of rank deficient.
Lingsheng Meng, Limin Li
doaj   +1 more source

Penalized partial least squares for pleiotropy

open access: yesBMC Bioinformatics, 2021
Background The increasing number of genome-wide association studies (GWAS) has revealed several loci that are associated to multiple distinct phenotypes, suggesting the existence of pleiotropic effects.
Camilo Broc   +2 more
doaj   +1 more source

Nonlinear least squares method

open access: yesCommunications, 1999
The paper deals with a comparison of linear and nonlinear least squares approximation. Its aim is to show that the well known transformations of nonlinear dependencies on linear dependencies do not always give exact results.
Jaromír Máca, Bohus Leitner
doaj   +1 more source

Generalized Least Squares and Weighted Least Squares Estimation Methods for Distributional Parameters

open access: yesRevstat Statistical Journal, 2015
Regression procedures are often used for estimating distributional parameters because of their computational simplicity and useful graphical presentation. However, the resulting regression model may have heteroscedasticity and/or correction problems and
Yeliz Mert Kantar
doaj   +1 more source

Unifying Least Squares, Total Least Squares and Data Least Squares [PDF]

open access: yes, 2002
The standard approaches to solving overdetermined linear systems A x ≈ b construct minimal corrections to the vector b and/or the matrix A such that the corrected system is compatible. In ordinary least squares (LS) the correction is restricted to b, while in data least squares (DLS) it is restricted to A. In scaled total least squares (Scaled TLS) [15]
Christopher C. Paige, Zdeněk Strakoš
openaire   +1 more source

Least squares data fitting

open access: yesCiencias Marinas, 2002
 It is desired to represent, as good as possible, a series of data by means of certain functions with free parameters. "As good as possible" means that these parameters ara chosen so that the residuals, the difference between data and fitting functions,
P Ripa
doaj   +1 more source

Comparison between total least squares and ordinary least squares in obtaining the linear relationship between stable water isotopes

open access: yesGeoscience Letters, 2022
The linear relationship between two stable water isotopes (δD and δ18O) has been used to examine the physical processes and movements or changes of three water phases (water vapor, liquid water and ice), including deuterium excess.
Jeonghoon Lee   +3 more
doaj   +1 more source

Total Least Squares Spline Approximation

open access: yesMathematics, 2019
Spline approximation, using both values y i and x i as observations, is of vital importance for engineering geodesy, e.g., for approximation of profiles measured with terrestrial laser scanners, because it enables the consideration of
Frank Neitzel   +2 more
doaj   +1 more source

Chebyshev Approximations by Least Squares Method

open access: yesИзвестия Иркутского государственного университета: Серия "Математика", 2020
We consider the problem of linear approximation in the form of the minimization problem of the weighted Chebyshev norm, and that in the form of the minimization problem of the weighted Euclidean norm of the residual vector.
V.I. Zorkaltsev, E. V. Gubiy
doaj   +1 more source

Differentially Private Ordinary Least Squares

open access: yesThe 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

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