A sequential test for variable selection in high dimensional complex data
type: Item
instance of: scholarly article
title: A sequential test for variable selection in high dimensional complex data
author: Kofi P. Adragni
author: Moumita Karmakar
published in: Computational Statistics and Data Analysis
publication date: 2018-11-23T00:00:00Z
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 62H25
Mathematics Subject Classification ID: 62L10
zbMATH DE Number: 6984099
zbMATH Keywords: inverse regression
zbMATH Keywords: dimension reduction
zbMATH Keywords: principal components
zbMATH Keywords: variable selection
zbMATH Keywords: variable screening
zbMATH Keywords: high dimensionality
zbMATH Keywords: data analysis
describes a project that uses: R
describes a project that uses: RSIR
describes a project that uses: glmnet
describes a project that uses: spls
describes a project that uses: ldr
MaRDI profile type: Publication
full work available at URL: j.csda.2014.07.016
OpenAlex ID: W2044541520
cites work: Sufficient dimension reduction and prediction in regression
cites work: Better Subset Regression Using the Nonnegative Garrote
cites work: The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
cites work: Coordinate-independent sparse sufficient dimension reduction and variable selection
cites work: Sparse Partial Least Squares Regression for Simultaneous Dimension Reduction and Variable Selection
cites work: Q4217298
cites work: Testing predictor contributions in sufficient dimension reduction.
cites work: Fisher lecture: Dimension reduction in regression
cites work: Principal fitted components for dimension reduction in regression
cites work: Q3678498
cites work: De-noising by soft-thresholding
cites work: Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
cites work: Sure Independence Screening for Ultrahigh Dimensional Feature Space
cites work: Q3431917
cites work: Sliced Inverse Regression for Dimension Reduction
cites work: On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
cites work: Sparse sufficient dimension reduction
cites work: On Directional Regression for Dimension Reduction
cites work: Sliced Inverse Regression with Regularizations
cites work: Q4864293
cites work: Sparse sufficient dimension reduction using optimal scoring
cites work: Positive-Definite ℓ1-Penalized Estimation of Large Covariance Matrices
cites work: Regularization and Variable Selection Via the Elastic Net
DOI: 10.1016/J.CSDA.2014.07.016
Recommended article: Consistent variable selection in high dimensional regression via multiple testing
Recommended article: Efficient test-based variable selection for high-dimensional linear models
Recommended article: SEQUENTIAL, BOTTOM‐UP VARIABLE SELECTION FOR HIGH‐DIMENSIONAL CLASSIFICATION
Recommended article: A sequential approach to feature selection in high-dimensional additive models
Recommended article: High-dimensional linear model selection motivated by multiple testing
Recommended article: Variable selection in high dimensional data analysis with applications
Recommended article: Variable selection for high dimensional multivariate outcomes
Recommended article: A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models
Recommended article: A Test for Multivariate Analysis of Variance in High Dimension
Recommended article: Q4298357
description: scientific article; zbMATH DE number 6984099