A sparse additive model for high-dimensional interactions with an exposure variable
From MaRDI portal
Publication:6111496
DOI10.1016/j.csda.2022.107624MaRDI QIDQ6111496
Kieran O'Donnell, Tianyuan Lu, Amanda Lovato, Unnamed Author, Archer Y. Yang, Michael J. Meaney, Michael S. Kobor, David L. Olds, Celia M. T. Greenwood
Publication date: 7 July 2023
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
high-dimensional datavariable selectiongene-environment interactionblockwise coordinate descentstrong heredity property
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The Adaptive Lasso and Its Oracle Properties
- A lasso for hierarchical interactions
- Statistics for high-dimensional data. Methods, theory and applications.
- Component selection and smoothing in multivariate nonparametric regression
- Variable selection in nonparametric additive models
- The composite absolute penalties family for grouped and hierarchical variable selection
- On the asymptotic properties of the group lasso estimator for linear models
- On the adaptive elastic net with a diverging number of parameters
- Interaction
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Sparse Additive Models
- Bayesian variable selection with related predictors
- Model Selection for High-Dimensional Quadratic Regression via Regularization
- Regression coefficient and autoregressive order shrinkage and selection via the lasso
- Variable Selection With the Strong Heredity Constraint and Its Oracle Property
- Variable Selection Using Adaptive Nonlinear Interaction Structures in High Dimensions
- Nonparametric regression with adaptive truncation via a convex hierarchical penalty
- Structured sparsity through convex optimization