搜索结果: 31-41 共查到“统计学 Lasso”相关记录41条 . 查询时间(0.052 秒)
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 l...
LASSO, Iterative Feature Selection and the Correlation Selector: Oracle inequalities and numerical performances
Regression estimation statistical learning confidence regions shrinkage and thresholding methods LASSO
2009/9/16
We propose a general family of algorithms for regression estimation with quadratic loss, on the basis of geometrical considerations. These algorithms are able to select relevant functions into a large...
On the asymptotic properties of the group lasso estimator for linear models
Least Squares Sparsity Group-Lasso Model Selection Oracle Inequalities Persistence
2009/9/16
We establish estimation and model selection consistency, prediction and estimation bounds and persistence for the group-lasso estimator and model selector proposed by Yuan and Lin (2006) for least squ...
Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators
Linear model Lasso Dantzig Sparsity Model selection Sign consistency
2009/9/16
We derive the l∞ convergence rate simultaneously for Lasso and Dantzig estimators in a high-dimensional linear regression model under a mutual coherence assumption on the Gram matrix of the design and...
On lasso for censored data
Accelerated failure time model Buckley-James estimator least angle regression survival analysis synthetic data
2009/9/16
In this paper, we propose a new lasso-type estimator for censored data after one-step imputatation. While several penalized likelihood estimators have been proposed for censored data variable selectio...
Adaptive Lasso for High Dimensional Regression and Gaussian Graphical Modeling
Adaptive Lasso High Dimensional Regression Gaussian Graphical Modeling
2010/3/18
We show that the two-stage adaptive Lasso procedure (Zou, 2006) is consistent for high-dimensional
model selection in linear and Gaussian graphical models. Our conditions for consistency cover more
...
The sparsity and bias of the Lasso selection in high-dimensional linear regression
Penalized regression high-dimensional data variable selection bias rate consistency spectral analysis random matrices
2010/4/30
Meinshausen and Buhlmann [Ann. Statist. 34 (2006) 1436–1462]
showed that, for neighborhood selection in Gaussian graphical models,
under a neighborhood stability condition, the LASSO is consistent,
...
Variable Selection Incorporating Prior Constraint Information into Lasso
lasso linear models prior constraint information sample information variableselection
2010/4/29
We propose the variable selection procedure incorporating prior constraint information into
lasso. The proposed procedure combines the sample and prior information, and selects significant variables ...
Sparsity oracle inequalities for the Lasso
sparsity oracle inequalities Lasso penalized least squares nonparametric regression dimension reduction
2010/4/29
This paper studies oracle properties of ℓ1-penalized least squares
in nonparametric regression setting with random design. We show that the
penalized least squares estimator satisfies sparsity...
Lasso type classifiers with a reject option
Bayes classifiers classification convex surrogate loss empirical risk minimization hinge loss large margin classifiers
2010/4/29
We consider the problem of binary classification where one can,
for a particular cost, choose not to classify an observation. We present a
simple proof for the oracle inequality for the excess risk ...
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...