A new class of efficient and debiased two-step shrinkage estimators: method and application

DOI10.1080/02664763.2021.1973389OpenAlexW3200939596MaRDI QIDQ5056940

B. M. Golam Kibria, Muhammad Qasim, Pär Sjölander, Kristofer Månsson

Publication date: 8 December 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2021.1973389

zbMATH Keywords

Monte Carlo simulationsridge regressionmulticollinearitytwo-parameter estimatorchemical structuresdebiased estimator

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Cites Work

• Unnamed Item
• A class of almost unbiased and efficient estimators of regression coefficients
• Rank-based Liu regression
• Boosting ridge regression
• Some improved estimation strategies in high-dimensional semiparametric regression models with application to riboflavin production data
• A Simulation Study of Some Ridge Regression Estimators under Different Distributional Assumptions
• SLASSO: a scaled LASSO for multicollinear situations
• Mean squared error matrix comparisons between biased estimators — An overview of recent results
• On small sample properties of the almost unbiased generalized ridge estimator
• A Simulation Study of Some Ridge Estimators
• A Monte Carlo Evaluation of Some Ridge-Type Estimators
• A new class of blased estimate in linear regression
• REVIEW AND CLASSIFICATIONS OF THE RIDGE PARAMETER ESTIMATION TECHNIQUES
• Theory of Ridge Regression Estimation with Applications
• Performance of Some New Ridge Regression Estimators
• Using Liu-Type Estimator to Combat Collinearity
• On the performance of some new Liu parameters for the gamma regression model
• New ridge estimators in the inverse Gaussian regression: Monte Carlo simulation and application to chemical data
• On some beta ridge regression estimators: method, simulation and application
• Performance of some new Liu parameters for the linear regression model
• Efficiency of an almost unbiased two-parameter estimator in linear regression model
• The Restricted and Unrestricted Two-Parameter Estimators
• Ridge Regression: Biased Estimation for Nonorthogonal Problems

This page was built for publication: A new class of efficient and debiased two-step shrinkage estimators: method and application