Results 1 to 10 of about 601,721 (146)

Pointwise error estimates in localization microscopy [PDF]

open access: yesNature Communications, 2017
Super-resolution localization microscopy produces biophysical information in the form of estimated positions of single molecules. Here, Lindénet al. estimate the uncertainty of single localizations, and show that this additional information can improve ...
Martin Lindén   +3 more
doaj   +2 more sources

Error Estimates for Doubly-Generalized Tikhonov-Phillips Regularization

open access: yesTrends in Computational and Applied Mathematics, 2023
In this work, error estimates are presented for the case in which the regularized solution is obtained by minimizing doubly-generalized Tikhonov-Phillips functionals. The first result is based mainly on an assumption given by a source condition.
M. J. Carrió   +2 more
doaj   +1 more source

Robust Relative Error Estimation [PDF]

open access: yesEntropy, 2018
Relative error estimation has been recently used in regression analysis. A crucial issue of the existing relative error estimation procedures is that they are sensitive to outliers. To address this issue, we employ the γ -likelihood function, which is constructed through γ -cross entropy with keeping the original statistical model in use. The
Kei Hirose, Hiroki Masuda
openaire   +4 more sources

Gauss–Newton–Secant Method for Solving Nonlinear Least Squares Problems under Generalized Lipschitz Conditions

open access: yesAxioms, 2021
We develop a local convergence of an iterative method for solving nonlinear least squares problems with operator decomposition under the classical and generalized Lipschitz conditions. We consider the case of both zero and nonzero residuals and determine
Ioannis K. Argyros   +4 more
doaj   +1 more source

Goal Oriented Time Adaptivity Using Local Error Estimates

open access: yesAlgorithms, 2020
We consider initial value problems (IVPs) where we are interested in a quantity of interest (QoI) that is the integral in time of a functional of the solution. For these, we analyze goal oriented time adaptive methods that use only local error estimates.
Peter Meisrimel, Philipp Birken
doaj   +1 more source

On the Convergence of a New Family of Multi-Point Ehrlich-Type Iterative Methods for Polynomial Zeros

open access: yesMathematics, 2021
In this paper, we construct and study a new family of multi-point Ehrlich-type iterative methods for approximating all the zeros of a uni-variate polynomial simultaneously.
Petko D. Proinov, Milena D. Petkova
doaj   +1 more source

Radial Point Interpolation-Based Error Recovery Estimates for Finite Element Solutions of Incompressible Elastic Problems

open access: yesApplied Sciences, 2023
Error estimation and adaptive applications help to control the discretization errors in finite element analysis. The study implements the radial point interpolation (RPI)-based error-recovery approaches in finite element analysis.
Nabil Ben Kahla   +2 more
doaj   +1 more source

CAVEAT ON THE ERROR ANALYSIS FOR STEREOLOGICAL ESTIMATES

open access: yesImage Analysis and Stereology, 2011
It is frequently asked that how big a sample size, or how much measurement, is needed to achieve an accuratestereological estimate. The observed total error of a stereological estimate arises from individual difference (i.e.
Zhengwei Yang   +3 more
doaj   +1 more source

Errors on errors – Estimating cosmological parameter covariance [PDF]

open access: yesProceedings of the International Astronomical Union, 2014
AbstractCurrent and forthcoming cosmological data analyses share the challenge of huge datasets alongside increasingly tight requirements on the precision and accuracy of extracted cosmological parameters. The community is becoming increasingly aware that these requirements not only apply to the central values of parameters but, equally important, also
Joachimi, Benjamin, Taylor, Andy
openaire   +2 more sources

Cardinal approximation of functions by splines on an interval

open access: yesMathematical Modelling and Analysis, 2009
The cardinal interpolant of functions on the real line by splines is determined by certain formula free of solving large or infinite systems. We apply this formula to functions given on the interval [0,1] introducing special extensions of functions from [
Gennadi Vainikko
doaj   +1 more source

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