Minimal Penalties for Gaussian Model Selection

2006/07/04 by Lucien Birgé, Pascal Massart · 1 citation
Engineering · Mathematics · #Algorithm #Applied mathematics #Artificial intelligence #Computer science #Constant (computer programming) #Control Systems and Identification #Estimator #Fault Detection and Control Systems #Gaussian #Least-squares function approximation #Mathematical optimization #Mathematics #Minification #Model selection #Penalty method #Piecewise #Selection (genetic algorithm) #Statistical Methods and Inference #Statistics #Upper and lower bounds

paper · pdf · doi:10.1007/s00440-006-0011-8

crossref issued 2006/07/04 · crossref published 2006/07/04 · crossref published-online 2006/07/04 · openalex publication_date 2006/07/04 · crossref created 2006/07/04 · crossref published-print 2007/05/01 · crossref deposited 2022/05/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29 · crossref indexed 2026/08/04

Citations

• Regression and time series model selection in small samples
• Can the strengths of AIC and BIC be shared? A conflict between model indentification and regression estimation
• A course of modern analysis an introduction to the general theory of infinite processes and of analytic functions with an account of the principal transcendental functions
• Least angle regression
• Adapting to unknown sparsity by controlling the false discovery rate
• A new look at the statistical model identification
• Probability Inequalities for Sums of Bounded Random Variables

Cited by

• Concentration inequalities and cut-off phenomena for penalized model selection within a basic Rademacher framework