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A Globally Convergent Method For Nonlinear Least-squares Problems Based On The Gauss-newton Model With Spectral Correction
(Univ Simon BolivarCaracas, 2016)
Local convergence analysis of proximal Gauss-Newton method for penalized nonlinear least squares problems
We present a local convergence analysis of the proximal Gauss-Newton method for solving penalized nonlinear least squares problems in a Hilbert space setting. Using more precise majorant conditions than in earlier studies ...
Proximal Gauss-Newton method
In this chapter we extend the solvability of penalized nonlinear least squares problems using the proximal Gauss–Newton method. Moreover, a numerical example validating the theoretical results is also presented.
Estimation of Endogenous Volatility Models with Exponential Trends
(MDPI, 2022)
Nonlinearities, exponential trends, and Euler equations are three key features of standard dynamic volatility models of speculation, economic growth, or macroeconomic fluctuations with occasionally binding constraints and ...
Algebraic Rules For Computing The Regularization Parameter Of The Levenberg-marquardt Method
(SpringerNew York, 2016)
An Algorithm For Solving Sparse Nonlinear Least Squares Problems
(Springer-Verlag, 1987)
An Algorithm For Solving Nonlinear Least-squares Problems With A New Curvilinear Search
(Springer-Verlag, 1990)
Vis-NIR spectrometric determination of Brix and sucrose in sugar production samples using kernel partial least squares with interval selection based on the successive projections algorithm
(Elsevier Science, 2018-05)
This paper proposes a new variable selection method for nonlinear multivariate calibration, combining the Successive Projections Algorithm for interval selection (iSPA) with the Kernel Partial Least Squares (Kernel-PLS) ...