A General Class of Estimators for the Linear Regression Model Affected by Collinearity and Outliers
From MaRDI portal
Publication:3578978
DOI10.1080/03610911003695719zbMath1192.62170OpenAlexW2086267204MaRDI QIDQ3578978
Pedro Macedo, Elvira Silva, Manuel G. Scotto
Publication date: 5 August 2010
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610911003695719
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Guest editorial. Information and entropy econometrics -- volume overview and synthesis
- Bayesian methods and maximum entropy for ill-posed inverse problems
- Information and entropy econometrics -- editor's view.
- Comparison of maximum entropy and higher-order entropy estimators.
- Comparative statics of the generalized maximum entropy estimator of the general linear model
- A generalized information theoretical approach to tomographic reconstruction
- On a Measure of the Information Provided by an Experiment
- Information Theory and Statistical Mechanics
- Least Median of Squares Regression
- On Some Ridge Regression Estimators: An Empirical Comparisons
- Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
- Leverage and Breakdown in L 1 Regression
- Ridge regression:some simulations
- A new class of blased estimate in linear regression
- Using Liu-Type Estimator to Combat Collinearity
- Robust Statistics
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- On Information and Sufficiency
- Certain Inequalities in Information Theory and the Cramer-Rao Inequality
This page was built for publication: A General Class of Estimators for the Linear Regression Model Affected by Collinearity and Outliers
