The \(\mathrm{r}\)-\(\mathrm{d}\) class predictions in linear mixed models

DOI10.1515/jiip-2019-0069zbMath1470.62106OpenAlexW3042824526MaRDI QIDQ2048216

Özge Kuran

Publication date: 5 August 2021

Published in: Journal of Inverse and Ill-Posed Problems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/jiip-2019-0069

zbMATH Keywords

multicollinearitybest linear unbiased predictorprincipal components regression predictor\(\mathrm{r}\)-\(\mathrm{d}\) class predictorLiu predictor

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Multi-parameter Tikhonov regularization
• The convergence rate of a regularized ranking algorithm
• Direct estimation of linear functionals from indirect noisy observations
• Nonnegative and positive definiteness of matrices modified by two matrices of rank one
• On regularization algorithms in learning theory
• Superiority of the \(r\)-\(d\) class estimator over some estimators by the mean square error matrix criterion
• Multi-parameter regularization techniques for ill-conditioned linear systems
• Adaptive estimation of linear functionals in Hilbert scales from indirect white noise observa\-tions
• That BLUP is a good thing: The estimation of random effects. With comments and a rejoinder by the author
• A linear functional strategy for regularized ranking
• Principal components regression and \(r-k\) class predictions in linear mixed models
• Principal component analysis.
• Linear models. Least squares and alternatives
• Combining the Liu-type estimator and the principal component regression estimator
• Learning theory estimates via integral operators and their approximations
• A Small Area Predictor under Area-Level Linear Mixed Models with Restrictions
• A Monte Carlo Evaluation of Some Ridge-Type Estimators
• Good ridge estimators based on prior information
• A new class of blased estimate in linear regression
• Average Information REML: An Efficient Algorithm for Variance Parameter Estimation in Linear Mixed Models
• Mixed-Effects Models in S and S-PLUS
• COMBINING THE LIU ESTIMATOR AND THE PRINCIPAL COMPONENT REGRESSION ESTIMATOR
• Using Liu-Type Estimator to Combat Collinearity
• 10.1162/1532443041827916
• Bayes Factors
• Approximate inverse for linear and some nonlinear problems
• A further prediction method in linear mixed models: Liu prediction
• The r – d class estimator in generalized linear models: applications on gamma, Poisson and binomial distributed responses
• An evaluation of ridge estimator in linear mixed models: an example from kidney failure data
• A Further Study of Predictions in Linear Mixed Models
• On the Principal Component Liu-type Estimator in Linear Regression
• General ridge predictors in a mixed linear model
• Subset Ranking Using Regression
• The Estimation of Environmental and Genetic Trends from Records Subject to Culling
• The Restricted and Unrestricted Two-Parameter Estimators
• Aggregation of regularized solutions from multiple observation models
• A generalized multivariate analysis of variance model useful especially for growth curve problems
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Linear Statistical Inference and its Applications

This page was built for publication: The \(\mathrm{r}\)-\(\mathrm{d}\) class predictions in linear mixed models