Shrinkage and penalized estimators in weighted least absolute deviations regression models

DOI10.1080/00949655.2018.1441415OpenAlexW2791710468MaRDI QIDQ4960627

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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/10.1080/00949655.2018.1441415

zbMATH Keywords

outliers Monte Carlo simulation shrinkage asymptotic distributional risk asymptotic distributional bias pretest WLAD-Lasso

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

A comparison of preliminary test, Stein-type and penalty estimators in gamma regression model

Uses Software

ElemStatLearn

Cites Work

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Leverage and Breakdown in L 1 Regression
Improved Estimation in a Contingency Table: Independence Structure
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
Shrinkage estimation in lognormal regression model for censored data
Application of shrinkage estimation in linear regression models with autoregressive errors
A mathematical programming approach for improving the robustness of least sum of absolute deviations regression
A Semiparametric Basis for Combining Estimation Problems Under Quadratic Loss

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