Normalized and standard Dantzig estimators: two approaches

DOI10.1214/15-EJS1040zbMath1327.62408OpenAlexW1546194496MaRDI QIDQ491397

Hubert Szymanowski, Jan Mielniczuk

Publication date: 25 August 2015

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ejs/1434988476

zbMATH Keywords

constrained optimizationlinear modelnormalizationhigh dimensionalityKarush-Kuhn-Tucker conditionsDantzig selectorLASSO

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Convex programming (90C25)

Cites Work

• Unnamed Item
• Statistics for high-dimensional data. Methods, theory and applications.
• The Dantzig selector and sparsity oracle inequalities
• Near-ideal model selection by \(\ell _{1}\) minimization
• On the conditions used to prove oracle results for the Lasso
• Simultaneous analysis of Lasso and Dantzig selector
• Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators
• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• DASSO: Connections Between the Dantzig Selector and Lasso

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