Controlling Variable Selection by the Addition of Pseudovariables
From MaRDI portal
Publication:5307699
DOI10.1198/016214506000000843zbMath1284.62242OpenAlexW2094231493MaRDI QIDQ5307699
Yujun Wu, Dennis D. Boos, Leonard A. Stefanski
Publication date: 18 September 2007
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: http://www.lib.ncsu.edu/resolver/1840.16/5883
Related Items
Robust feature screening for high-dimensional survival data, A Bottom-Up Approach to Testing Hypotheses That Have a Branching Tree Dependence Structure, With Error Rate Control, Variable Selection via Regression Trees in the Presence of Irrelevant Variables, Fast FSR Variable Selection with Applications to Clinical Trials, A relative error-based approach for variable selection, Probing for sparse and fast variable selection with model-based boosting, Inference for the Dimension of a Regression Relationship Using Pseudo-Covariates, Double Empirical Bayes Testing, Variable selection by searching for good subsets, FSR methods for second-order regression models, Variable Selection in Semiparametric Linear Regression with Censored Data, On consistency and sparsity for sliced inverse regression in high dimensions, A two-component \(G\)-prior for variable selection, SimSel: a new simulation method for variable selection, A statistical analysis of multiple temperature proxies: are reconstructions of surface temperatures over the last 1000 years reliable?, Kernel Knockoffs Selection for Nonparametric Additive Models, Simultaneous Factor Selection and Collapsing Levels in ANOVA, Discussion of the Paper ”Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models” by Søren Johansen and Bent Nielsen, A simple forward selection procedure based on false discovery rate control, Robust adaptive Lasso for variable selection, Objective Bayesian variable selection in linear regression model, Advanced topics in sliced inverse regression, Model selection and inference for censored lifetime medical expenditures, Unrestricted permutation forces extrapolation: variable importance requires at least one more model, or there is no free variable importance, A knockoff filter for high-dimensional selective inference
