Penalized linear regression for discrete ill-posed problems: A hybrid least-squares and mean-squared error approach

Mathematics

• Least Square 100%
• Linear Regression 100%
• Squared Error 100%
• Posed Problem 100%
• Matrix 66%
• Regularization 66%
• Singular Value 33%
• Model Matrix 33%
• Minimizes 33%
• Linear Least Squares 33%

Keyphrases

• Discrete Ill-posed Problem 100%
• Penalized Regression 100%
• Linear Least-squares 33%
• Artificial Perturbation 33%
• Perturbation Matrix 33%
• Benchmarking Method 33%
• Discrete Ill-posed 33%
• Ill-posed Model 33%
• Model Matrix 33%
• Value Structure 33%