SIMULTANEOUS ANALYSIS OF LASSO AND DANTZIG

By Peter J. Bickel, Yaacov Ritov, Alexandre B. Tsybakov. 2007

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1. Jürg Schelldorfer
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3. Peter Buhlmann
4. Bryan T. Kelly
5. Matt Taddy
6. S. De Geer
7. Kathleen T. Li
8. David R. Bell

Citations in the corpus

• Estimation for High‐Dimensional Linear Mixed‐Effects Models Using ℓ1‐Penalization (2010, methodology): “A discussion of this assumption can be found in Bickel et al. (2009) and van de Geer & Bühlmann (2009). Define”
• Estimation of average treatment effects with panel data: Asymptotic theory and implementation (2017, methodology): “It is well established that the LASSO method allows for the number of regressors to be larger than the sample size (Meinshausen and Yu, 2009; Bickel et al., 2009).”
• Text as Data (2017, methodology): “, Bickel et al. 2009; Wainwright 2009; Belloni et al. 2011; Buhlmann and van de Geer 2011), and the number of nonzero estimated coefficients is an unbiased estimator of the regression degrees of freedom (which is useful in model selection; see Zou et al. 2007). Penalties with a bias that diminishes ”