Robust logistic regression modelling via the elastic net-type regularization and tuning parameter selection
From MaRDI portal
Publication:5222417
DOI10.1080/00949655.2015.1073290OpenAlexW2291342904MaRDI QIDQ5222417
Publication date: 1 April 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2015.1073290
high-dimensional datainformation criteriatuning parameter selection\(\mathrm{L}_1\)-type regularizationrobust logisticregression
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Outlier identification in high dimensions
- Estimating the dimension of a model
- Information criteria and statistical modeling.
- Robust Coordinate Descent Algorithm Robust Solution Path for High-dimensional Sparse Regression Modeling
- Robust penalized logistic regression with truncated loss functions
- Robust Linear Model Selection Based on Least Angle Regression
- Penalized logistic regression for detecting gene interactions
- Penalized maximum likelihood estimation in logistic regression and discrimination
- Generalised information criteria in model selection
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Regularization and Variable Selection Via the Elastic Net
- Tuning parameter selectors for the smoothly clipped absolute deviation method
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
Related Items (6)
Weighted Lasso estimates for sparse logistic regression: non-asymptotic properties with measurement errors ⋮ Robust variable selection in the logistic regression model ⋮ Outlier-resistant high-dimensional regression modelling based on distribution-free outlier detection and tuning parameter selection ⋮ Asymptotic behaviour of penalized robust estimators in logistic regression when dimension increases ⋮ Penalized robust estimators in sparse logistic regression ⋮ Robust logistic zero-sum regression for microbiome compositional data
This page was built for publication: Robust logistic regression modelling via the elastic net-type regularization and tuning parameter selection