Strong robust generalized cross-validation for choosing the regularization parameter

DOI10.1088/0266-5611/24/3/034006zbMath1137.62018OpenAlexW4247667787MaRDI QIDQ3507910

Mark A. Lukas

Publication date: 24 June 2008

Published in: Inverse Problems (Search for Journal in Brave)

Full work available at URL: http://researchrepository.murdoch.edu.au/id/eprint/8804/

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35) Nonparametric estimation (62G05)

Related Items

Performance of Robust GCV and Modified GCV for Spline Smoothing ⋮ A framework for estimating potential fluid flow from digital imagery ⋮ Robust GCV choice of the regularization parameter for correlated data ⋮ A predictor-corrector iterated Tikhonov regularization for linear ill-posed inverse problems ⋮ Comparing parameter choice methods for regularization of ill-posed problems ⋮ Efficient algorithms for robust generalized cross-validation spline smoothing ⋮ Practical use of robust GCV and modified GCV for spline smoothing ⋮ Parameter Choices for Fast Harmonic Spline Approximation

Uses Software

• Regularization tools
• gss