Ranked sparsity: a cogent regularization framework for selecting and estimating feature interactions and polynomials
From MaRDI portal
Publication:61016
DOI10.1007/s10182-021-00431-7OpenAlexW3185992437MaRDI QIDQ61016
Ryan Andrew Peterson, Joseph E. Cavanaugh, Ryan A. Peterson, Joseph E. Cavanaugh
Publication date: 25 January 2022
Published in: AStA Advances in Statistical Analysis, AStA. Advances in Statistical Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2107.07594
Related Items (3)
Uses Software
Cites Work
- Unnamed Item
- Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection
- Nearly unbiased variable selection under minimax concave penalty
- The Adaptive Lasso and Its Oracle Properties
- A lasso for hierarchical interactions
- Estimating the dimension of a model
- IPF-LASSO: integrative \(L_1\)-penalized regression with penalty factors for prediction based on multi-omics data
- Adaptive Lasso estimators for ultrahigh dimensional generalized linear models
- Extended Bayesian information criteria for model selection with large model spaces
- Extending the Modified Bayesian Information Criterion (mBIC) to Dense Markers and Multiple Interval Mapping
- Regression and time series model selection in small samples
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Fast Stable Restricted Maximum Likelihood and Marginal Likelihood Estimation of Semiparametric Generalized Linear Models
- Bayesian variable selection with related predictors
- Model Selection for High-Dimensional Quadratic Regression via Regularization
- Marginal false discovery rate control for likelihood‐based penalized regression models
- Variable Selection With the Strong Heredity Constraint and Its Oracle Property
- Identification of biomarker‐by‐treatment interactions in randomized clinical trials with survival outcomes and high‐dimensional spaces
- Some Comments on C P
- Ordered quantile normalization: a semiparametric transformation built for the cross-validation era
- A new look at the statistical model identification
This page was built for publication: Ranked sparsity: a cogent regularization framework for selecting and estimating feature interactions and polynomials
