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Penalized estimation of high-dimensional models under a generalized sparsity cindition

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Publication:4921673
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DOI10.5705/ss.2010.290zbMath1433.62194OpenAlexW4252714277MaRDI QIDQ4921673

Joel L. Horowitz, Jian Huang

Publication date: 13 May 2013

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.5705/ss.2010.290


zbMATH Keywords

high-dimensional datavariable selectionpenalized regression


Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)


Related Items (6)

Using penalized likelihood to select parameters in a random coefficients multinomial logit model ⋮ Nonparametric estimation and inference under shape restrictions ⋮ Nonparametric inference for additive models estimated via simplified smooth backfitting ⋮ Linear and nonlinear signal detection and estimation in high-dimensional nonparametric regression under weak sparsity ⋮ Multiple structural breaks in cointegrating regressions: a model selection approach ⋮ Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions




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