Efficiency of the QR class estimator in semiparametric regression models to combat multicollinearity
From MaRDI portal
Publication:4960645
DOI10.1080/00949655.2018.1448088OpenAlexW2791653435MaRDI QIDQ4960645
Mahdi Roozbeh, Mohammad Najarian
Publication date: 23 April 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2018.1448088
Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Eigenvalues, singular values, and eigenvectors (15A18)
Related Items
Uncertain stochastic ridge estimation in partially linear regression models with elliptically distributed errors ⋮ Mixed spline smoothing and kernel estimator in biresponse nonparametric regression
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A class of biased estimators based on QR decomposition
- Efficiency of the modified jackknifed Liu-type estimator
- Improvement of the Liu estimator in linear regression model
- Mean square error matrix comparison of some estimators in linear regressions with multicollinearity
- Consistent covariate selection and post model selection inference in semiparametric regression.
- Optimal partial ridge estimation in restricted semiparametric regression models
- Shrinkage ridge estimators in semiparametric regression models
- Performance of Kibria's methods in partial linear ridge regression model
- Improved preliminary test and Stein-rule Liu estimators for the ill-conditioned elliptical linear regression model
- Linear models and generalizations. Least squares and alternatives. With contributions by Michael Schomaker.
- Optimal zone for bandwidth selection in semiparametric models
- Restricted Ridge Estimators of the Parameters in Semiparametric Regression Model
- A note on combining ridge and principal component regression
- A new class of blased estimate in linear regression
- COMBINING THE LIU ESTIMATOR AND THE PRINCIPAL COMPONENT REGRESSION ESTIMATOR
- Trace bounds on the solution of the algebraic matrix Riccati and Lyapunov equation
- Some Liu and ridge-type estimators and their properties under the ill-conditioned Gaussian linear regression model
- A Simulation Study on Some Restricted Ridge Regression Estimators
- Singular Ridge Regression With Stochastic Constraints
- Using improved estimation strategies to combat multicollinearity
- Ridge Regression: Biased Estimation for Nonorthogonal Problems