Asymptotic properties of Lasso+mLS and Lasso+Ridge in sparse high-dimensional linear regression (Q389956)

scientific article; zbMATH DE number 6248973

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English	Asymptotic properties of Lasso+mLS and Lasso+Ridge in sparse high-dimensional linear regression	scientific article; zbMATH DE number 6248973

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instance of

scholarly article

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title

Asymptotic properties of Lasso+mLS and Lasso+Ridge in sparse high-dimensional linear regression (English)

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Electronic Journal of Statistics

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publication date

22 January 2014

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full work available at URL

https://arxiv.org/abs/1306.5505

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zbMATH Keywords

irrepresentable condition

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Lasso+Ridge

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sparsity

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asymptotic unbiasedness

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asymptotic normality

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residual bootstrap

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describes a project that uses

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Least squares after model selection in high-dimensional sparse models

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$\ell_1$-penalized quantile regression in high-dimensional sparse models

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Asymptotic expansions for the power of distributionfree tests in the two- sample problem

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Some asymptotic theory for the bootstrap

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Q3311508

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Simultaneous analysis of Lasso and Dantzig selector

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Honest variable selection in linear and logistic regression models via $\ell _{1}$ and $\ell _{1}+\ell _{2}$ penalization

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Sparsity oracle inequalities for the Lasso

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The Dantzig selector: statistical estimation when $p$ is much larger than $n$. (With discussions and rejoinder).

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Bootstrapping Lasso Estimators

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Rates of convergence of the adaptive LASSO estimators to the oracle distribution and higher order refinements by the bootstrap

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Q4370586

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Contributions of empirical and quantile processes to the asymptotic theory of goodness-of-fit tests. (With comments)

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Stable recovery of sparse overcomplete representations in the presence of noise

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Bootstrap methods: another look at the jackknife

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Least angle regression. (With discussion)

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Q4318617

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Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties

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Bootstrapping regression models

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Pathwise coordinate optimization

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Recovery of Exact Sparse Representations in the Presence of Bounded Noise

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Model selection consistency of Dantzig selector

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Persistene in high-dimensional linear predictor-selection and the virtue of overparametrization

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Ridge Regression: Biased Estimation for Nonorthogonal Problems

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Asymptotic properties of bridge estimators in sparse high-dimensional regression models

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Q3543468

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Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators

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Asymptotics for Lasso-type estimators.

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MODEL SELECTION AND INFERENCE: FACTS AND FICTION

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A unified approach to model selection and sparse recovery using regularized least squares

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High-dimensional graphs and variable selection with the Lasso

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Relaxed Lasso

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Lasso-type recovery of sparse representations for high-dimensional data

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A Perturbation Method for Inference on Regularized Regression Estimates

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A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers

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On the distribution of the adaptive LASSO estimator

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Minimax Rates of Estimation for High-Dimensional Linear Regression Over $\ell_q$-Balls

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Q4864293

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Greed is Good: Algorithmic Results for Sparse Approximation

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High-dimensional generalized linear models and the lasso

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Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)

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The sparsity and bias of the LASSO selection in high-dimensional linear regression

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Q3174050

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The Adaptive Lasso and Its Oracle Properties

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Regularization and Variable Selection Via the Elastic Net

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Identifiers

zbMATH Open document ID

1281.62158

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DOI

10.1214/14-EJS875

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Mathematics Subject Classification ID

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Sitelinks

Mathematics(1 entry)

mardi Publication:389956