Penalized regression with ordinal predictors
From MaRDI portal
Publication:6573838
DOI10.1111/j.1751-5823.2009.00088.xMaRDI QIDQ6573838
Publication date: 17 July 2024
Published in: International Statistical Review (Search for Journal in Brave)
generalized linear modelsordinal predictorspenalized likelihood estimationgeneralized ridge regressionclassical linear modeldummy codingbasis function approach
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The generalized ridge estimator and improved adjustments for regression parameters
- Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
- Boosting a weak learning algorithm by majority
- The analysis of ordered categorical data: An overview and a survey of recent developments. (With discussion)
- Sequential Ordinal Modeling with Applications to Survival Data
- Anomalies in the Foundations of Ridge Regression
- Partial Proportional Odds Models for Ordinal Response Variables
- Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
- Boosting With theL2Loss
- Sparsity and Smoothness Via the Fused Lasso
- A bayesian analysis for a class of penalised likelihood estimates
- Ridge Estimators in Logistic Regression
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- Multivariate statistical modelling based on generalized linear models.
- The elements of statistical learning. Data mining, inference, and prediction
Related Items (4)
On the use of ordered factors as explanatory variables ⋮ A composite Bayesian approach for quantile curve fitting with non-crossing constraints ⋮ High-dimensional regression with ordered multiple categorical predictors ⋮ A Bayesian mixture model for changepoint estimation using ordinal predictors
This page was built for publication: Penalized regression with ordinal predictors
