Ridge estimation in linear mixed measurement error models using generalized maximum entropy

DOI10.1080/02331888.2022.2126474zbMath1497.62188OpenAlexW4296701980MaRDI QIDQ5044088

Fariba Janamiri, Abdolrahman Rasekh, Alireza Chaji, B. Babadi

Publication date: 24 October 2022

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888.2022.2126474

zbMATH Keywords

ridge regressiongeneralized maximum entropycollinearitylinear mixed measurement error modelsridge-GME estimation

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Generalized maximum entropy analysis of the linear simultaneous equations model
• Gilmour's approach to mixed and stochastic restricted ridge predictions in linear mixed models
• The data-constrained generalized maximum entropy estimator of the GLM: asymptotic theory and inference
• Hedonic housing prices and the demand for clean air
• Estimation in linear models with random effects and errors-in-variables
• Estimation of variance components in linear mixed measurement error models
• A generalized maximum entropy estimator to simple linear measurement error model with a composite indicator
• Comparative statics of the generalized maximum entropy estimator of the general linear model
• Corrected score function for errors-in-variables models: Methodology and application to generalized linear models
• On the Choice of the Ridge Parameter: A Maximum Entropy Approach
• A Monte Carlo Study of Recent Ridge Parameters
• On Some Ridge Regression Estimators: An Empirical Comparisons
• Ridge regression:some simulations
• A simulation study of ridge and other regression estimators
• Choosing Ridge Parameter for Regression Problems
• Performance of Some New Ridge Regression Estimators
• Ridge Regression and Generalized Maximum Entropy: An improved version of the Ridge–GME parameter estimator
• Two steps generalized maximum entropy estimation procedure for fitting linear regression when both covariates are subject to error
• An evaluation of ridge estimator in linear mixed models: an example from kidney failure data
• General ridge predictors in a mixed linear model
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Ridge estimation in linear mixed measurement error models with stochastic linear mixed restrictions