A random model approach for the LASSO
type: Item
instance of: scholarly article
title: A random model approach for the LASSO
zbMATH Open document ID: 1223.62116
author: Scott D. Foster
author: Arūnas P. Verbyla
author: Wayne S. Pitchford
published in: Computational Statistics
publication date: 2011-02-22T00:00:00Z
review text: The least absolute deviation and shrinkage operator (LASSO) method is considered for linear regression models. The authors concentrate on random effects models with Laplace distribution for the effects (unknown coefficients) where LASSO is equivalent to maximum likelihood and the choice of the regularization parameter in the LASSO penalty term can be made by the estimation of the erros and effect dispersions. An approximate marginal likelihood is derived for this estimation. A bootstrap-type procedure is described for the bias correction of the estimates. The performance of this approach and some other methods, such as cross-validation, forward and backward regression, is investigated via simulations. An application to prostate cancer data is presented.
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 62F40
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 5855582
zbMATH Keywords: least absolute selection and shrinkage operators
zbMATH Keywords: Laplace distribution
zbMATH Keywords: marginal likelihood maximization
zbMATH Keywords: bootstrap bias correction
cites work: S-PLUS
cites work: Least angle regression. (With discussion)
cites work: Q4360236
cites work: Ridge Regression: Biased Estimation for Nonorthogonal Problems
cites work: Newton-Raphson and Related Algorithms for Maximum Likelihood Variance Component Estimation
cites work: Q3203859
cites work: That BLUP is a good thing: The estimation of random effects. With comments and a rejoinder by the author
cites work: Q4864293
describes a project that uses: S-PLUS
describes a project that uses: R
MaRDI profile type: Publication
full work available at URL: s00180-007-0033-4
OpenAlex ID: W2085439484
DOI: 10.1007/S00180-007-0033-4
description: scientific article; zbMATH DE number 5855582