A priori weighting for parameter estimation

DOI10.1515/JIIP.2008.011zbMath1156.65008OpenAlexW2155579330MaRDI QIDQ3516727

Jodi L. Mead

Publication date: 11 August 2008

Published in: Journal of Inverse and Ill-posed Problems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/jiip.2008.011

zbMATH Keywords

algorithmparameter estimationnumerical examplesTikhonov regularizationmaximum likelihood estimatediscrete ill-posed problem\(\chi^2\) random variablenon-necessarily Gaussian noise

Mathematics Subject Classification ID

Random fields; image analysis (62M40) Point estimation (62F10) Ill-posedness and regularization problems in numerical linear algebra (65F22)

Related Items

Least squares problems with inequality constraints as quadratic constraints, Compact discrepancy and chi-squared principles for over-determined inverse problems, Learning spectral windowing parameters for regularization using unbiased predictive risk and generalized cross validation techniques for multiple data sets, \( \chi^2\) test for total variation regularization parameter selection, Priorconditioned CGLS-Based Quasi-MAP Estimate, Statistical Stopping Rule, and Ranking of Priors, Regularization parameter estimation for large-scale Tikhonov regularization using a priori information, Geophysical imaging of subsurface structures with least squares estimates

Uses Software

• Regularization tools

Cites Work

• Regularization tools: A Matlab package for analysis and solution of discrete ill-posed problems
• A Technique for the Numerical Solution of Certain Integral Equations of the First Kind
• Analysis of Discrete Ill-Posed Problems by Means of the L-Curve
• Tikhonov Regularization and Total Least Squares
• Covariance matrix selection and estimation via penalised normal likelihood