Results 11 to 20 of about 1,437,192 (281)

Approximate Least Squares [PDF]

open access: yes2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013
We present a novel iterative algorithm for approximating the linear least squares solution with low complexity. After a motivation of the algorithm we discuss the algorithm's properties including its complexity, and we present theoretical results as well
Huemer, Mario   +2 more
core   +2 more sources

Partitioned least squares [PDF]

open access: yesMachine Learning, 2019
AbstractLinear least squares is one of the most widely used regression methods in many fields. The simplicity of the model allows this method to be used when data is scarce and allows practitioners to gather some insight into the problem by inspecting the values of the learnt parameters.
Roberto Esposito   +2 more
openaire   +6 more sources

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

Robust linear least squares regression [PDF]

open access: yes, 2011
We consider the problem of robustly predicting as well as the best linear combination of $d$ given functions in least squares regression, and variants of this problem including constraints on the parameters of the linear combination.
Audibert, Jean-Yves, Catoni, Olivier
core   +6 more sources

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

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

Götterdämmerung over total least squares

open access: yesJournal of Geodetic Science, 2016
The traditional way of solving non-linear least squares (LS) problems in Geodesy includes a linearization of the functional model and iterative solution of a nonlinear equation system.
Malissiovas G., Neitzel F., Petrovic S.
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

GALS – Gradient Analysis by Least Squares [PDF]

open access: yesAnnales Geophysicae, 2008
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
doaj   +1 more source

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