Rejoinder to "Least angle regression" by Efron et al
英文摘要：
Rejoinder to ``Least angle regression'' by Efron et al. [math.ST/0406456]
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
继续探索
相关论文
Rejoinder to "Multivariate quantiles and multiple-output regression quantiles: From $L_1$ optimization to halfspace depth"
Rejoinder to "Multivariate quantiles and multiple-output regression quantiles: From $L_1$ optimization to halfspace depth" by M. Hallin, D. Paindaveine and M. Siman [arXiv:1002.4486]
math.STstat.TH
Discussion of "Least angle regression" by Efron et al
Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]
math.STstat.TH
Discussion of "Least angle regression" by Efron et al
Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]
math.STstat.TH
Discussion of "Least angle regression" by Efron et al
Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]
math.STstat.TH
Discussion of "Least angle regression" by Efron et al
Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]
math.STstat.TH
Discussion of "Least angle regression" by Efron et al
Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]
math.STstat.TH
更多相关论文收起更多论文
Discussion of "Least angle regression" by Efron et al
Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]
math.STstat.TH
Discussion of "Least angle regression" by Efron et al
Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]
math.STstat.TH
Discussion of "Least angle regression" by Efron et al
Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]
math.STstat.TH
Forward stagewise regression and the monotone lasso
We consider the least angle regression and forward stagewise algorithms for solving penalized least squares regression problems. In Efron, Hastie, Johnstone & Tibshirani (2004) it is proved that the least angle regression algorithm, with a small modification, solves the lasso regression problem. Here we give an analogous result for incremental forward stagewise regression, showing that it solves a version of the lasso problem that enforces monotonicity. One consequence of this is as follows: while lasso makes optimal progress in terms of reducing the residual sum-of-squares per unit increase i…
math.STstat.TH
新的解释和推断方法用于最小子角回归
New explanations and inference for least angle regression
本文提出了一种新的LAR推断方法，通过分析总体相关性参数的分布特性，提供了一种正式的停止规则和修改后的bootstrap方法，用于解释变量进入和不确定性量化。
math.STstat.MLstat.TH
