Optimal QR-based estimation in partially linear regression models with correlated errors using GCV criterion
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Publication:1662035
DOI10.1016/j.csda.2017.08.002zbMath1469.62134OpenAlexW2743442946MaRDI QIDQ1662035
Publication date: 17 August 2018
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2017.08.002
kernel smoothingQR decompositionmulticollinearityshrinkage parameterpartially linear regression modelgeneralized ridge estimation
Applications of statistics to economics (62P20) Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07)
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Cites Work
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- Robust ridge estimator in restricted semiparametric regression models
- Feasible ridge estimator in partially linear models
- Improving the estimators of the parameters of a probit regression model: a ridge regression approach
- Efficiency of the modified jackknifed Liu-type estimator
- Preliminary test Liu estimators based on the conflicting W, LR and LM tests in a regression model with multivariate Student-\(t\) error
- Efficiency of a Liu-type estimator in semiparametric regression models
- Difference based ridge and Liu type estimators in semiparametric regression models
- 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
- Semiparametric generalized least squares estimation in partially linear regression models with correlated errors
- Improved preliminary test and Stein-rule Liu estimators for the ill-conditioned elliptical linear regression model
- Statistical inference of partially linear regression models with heteroscedastic errors
- Ridge regression methodology in partial linear models with correlated errors
- 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 Simulation Study of Some Ridge Estimators
- Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
- A Monte Carlo Evaluation of Some Ridge-Type Estimators
- A new class of blased estimate in linear regression
- COMBINING THE LIU ESTIMATOR AND THE PRINCIPAL COMPONENT REGRESSION ESTIMATOR
- Singular Ridge Regression With Stochastic Constraints
- Improvement of the Liu Estimator in Weighted Mixed Regression
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias
