VIF-based adaptive matrix perturbation method for heteroskedasticity-robust covariance estimators in the presence of multicollinearity
type: Item
instance of: scholarly article
title: VIF-based adaptive matrix perturbation method for heteroskedasticity-robust covariance estimators in the presence of multicollinearity
zbMATH Open document ID: 1368.62194
DOI: 10.1080/03610926.2015.1060340
author: Chien-Chia Liäm Huang
author: Yow-Jen Jou
author: Hsun-Jung Cho
publication date: 2017-07-27T00:00:00Z
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 62J20
zbMATH DE Number: 6754414
zbMATH Keywords: collinearity
zbMATH Keywords: linear regression
zbMATH Keywords: matrix theory
zbMATH Keywords: optimization
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1080/03610926.2015.1060340
OpenAlex ID: W2340922188
cites work: Ridge estimation in linear models with heteroskedastic errors
cites work: Performance of Kibria's Method for the Heteroscedastic Ridge Regression Model: Some Monte Carlo Evidence
cites work: Using Heteroscedasticity-Consistent Standard Errors for the Linear Regression Model with Correlated Regressors
cites work: Q3938378
cites work: Generalized autoregressive conditional heteroscedasticity
cites work: New heteroskedasticity-robust standard errors for the linear regression model
cites work: Inference Under Heteroskedasticity and Leveraged Data
cites work: Inequalities for the trace of matrix product
cites work: VIF Regression: A Fast Regression Algorithm for Large Data
cites work: Using Liu-Type Estimator to Combat Collinearity
cites work: A New Asymmetric Interaction Ridge (AIR) Regression Method
cites work: The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses
published in: Communications in Statistics: Theory and Methods
description: scientific article; zbMATH DE number 6754414