Uncertain stochastic ridge estimation in partially linear regression models with elliptically distributed errors
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Publication:5110804
DOI10.1080/02331888.2020.1764558zbMath1440.62134OpenAlexW3024468515MaRDI QIDQ5110804
Mahdi Roozbeh, Nor Aishah Hamzah
Publication date: 23 May 2020
Published in: Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331888.2020.1764558
kernel smoothingmulticollinearitypartially linear regression modelStein-type shrinkageuncertain stochastic ridge estimation
Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)
Related Items (3)
Generalized difference-based weighted mixed almost unbiased liu estimator in semiparametric regression models ⋮ Unnamed Item ⋮ New restricted Liu estimator in a partially linear model
Cites Work
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- Robust ridge estimator in restricted semiparametric regression models
- A class of biased estimators based on QR decomposition
- Feasible ridge estimator in partially linear models
- Difference-based ridge estimator of parameters in partial linear model
- Preliminary test and Stein estimations in simultaneous linear equations
- Difference based ridge and Liu type estimators in semiparametric regression models
- Optimal QR-based estimation in partially linear regression models with correlated errors using GCV criterion
- Generalized difference-based weighted mixed almost unbiased ridge estimator in partially linear models
- Optimal partial ridge estimation in restricted semiparametric regression models
- Shrinkage ridge estimators in semiparametric regression models
- Ridge estimation in semi-parametric regression models under the stochastic restriction and correlated elliptically contoured errors
- A note on classical Stein-type estimators in elliptically contoured models
- Improved preliminary test and Stein-rule Liu estimators for the ill-conditioned elliptical linear regression model
- Estimation of parameters of parallelism model with elliptically distributed errors
- Shrinkage ridge regression in partial linear models
- Elliptically Contoured Models in Statistics and Portfolio Theory
- Feasible Ridge Estimator in Seemingly Unrelated Semiparametric Models
- Ridge Estimation under the Stochastic Restriction
- Restricted Ridge Estimators of the Parameters in Semiparametric Regression Model
- Semiparametric Ridge Regression Approach in Partially Linear Models
- On Some Ridge Regression Estimators: An Empirical Comparisons
- Comment on Ridge Estimation to the Restricted Linear Model
- A new estimator combining the ridge regression and the restricted least squares methods of estimation
- A weighted stochastic restricted ridge estimator in partially linear model
- On the ridge regression estimator with sub-space restriction
- Shrinkage Estimation in Restricted Elliptical Regression Model
- Performance analysis of the preliminary test estimator with series of stochastic restrictions
- Some Liu and ridge-type estimators and their properties under the ill-conditioned Gaussian linear regression model
- Efficiency of the QR class estimator in semiparametric regression models to combat multicollinearity
- On ridge parameter estimators under stochastic subspace hypothesis
- A revised Cholesky decomposition to combat multicollinearity in multiple regression models
- Least trimmed squares ridge estimation in partially linear regression models
- On the Use of Incomplete Prior Information in Regression Analysis
- Theory of Preliminary Test and Stein‐Type Estimation With Applications
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- Estimation and decision for linear systems with elliptical random processes
- An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias
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