On grouping effect of elastic net
Grouping effect of the elastic net asserts that coefficients corresponding to highly correlated predictors in a linear regression setting have small differences. A quantitative estimate for such small differences was given in Zou and Hastie (2005) when the coefficients have the same sign. We show that the same estimate holds true even when the coefficients have different signs. The estimate is also improved by means of an empirical approximation error when the model fits the data well.
Year of publication: |
2013
|
---|---|
Authors: | Zhou, Ding-Xuan |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 83.2013, 9, p. 2108-2112
|
Publisher: |
Elsevier |
Subject: | Elastic net | Grouping effect | Approximation error | Variable selection | Reproducing kernel Hilbert space |
Saved in:
Online Resource
Saved in favorites
Similar items by subject
-
Penalized regression with correlation based penalty
Tutz, Gerhard, (2006)
-
Variable selection for varying-coefficient models with the sparse regularization
Matsui, Hidetoshi, (2015)
-
Oracle Inequalities for Convex Loss Functions with Non-Linear Targets
Caner, Mehmet, (2013)
- More ...