A new heteroskedasticity-consistent covariance matrix estimator for the linear regression model

DOI10.1007/s10182-010-0141-2zbMath1477.62172OpenAlexW2069899827MaRDI QIDQ90764

Wilton Bernardino da Silva, Francisco Cribari-Neto, Wilton Bernardino da Silva, Francisco Cribari-Neto

Publication date: 4 November 2010

Published in: AStA Advances in Statistical Analysis, AStA. Advances in Statistical Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10182-010-0141-2

zbMATH Keywords

linear regressionheteroskedasticitycovariance matrix estimationquasi-\(t\) test

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05)

Related Items (12)

Finite-sample refinement of GMM approach to nonlinear models under heteroskedasticity of unknown form ⋮ Heteroskedastic linear regression model with compositional response and covariates ⋮ Alternative HAC covariance matrix estimators with improved finite sample properties ⋮ Addressing the distributed lag models with heteroscedastic errors ⋮ Testing inference in heteroskedastic linear regressions: a comparison of two alternative approaches ⋮ Incremental localization algorithm based on regularized iteratively reweighted least square ⋮ Linear regression estimation methods for inferring standard values of snow load in small sample situations ⋮ Some improvements in confidence intervals for standardized regression coefficients ⋮ Linear regression: robust heteroscedastic confidence bands that have some specified simultaneous probability coverage ⋮ skedastic ⋮ Efficient estimation of distributed lag model in presence of heteroscedasticity of unknown form: A Monte Carlo evidence ⋮ A new heteroskedasticity-consistent covariance matrix estimator and inference under heteroskedasticity

Uses Software

• Ox

Cites Work

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• Computing the distribution of quadratic forms in normal variables
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