Testing for normality in linear regression models using regression and scale equivariant estimators

DOI10.1016/j.econlet.2013.11.017zbMath1293.62150OpenAlexW3123179483MaRDI QIDQ2512346

Rami V. Tabri

Publication date: 7 August 2014

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.econlet.2013.11.017

zbMATH Keywords

linear regressionMonte Carlo testnormality testregression and scale equivariant estimators

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Hypothesis testing in multivariate analysis (62H15)

Cites Work

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• Monte Carlo tests with nuisance parameters: a general approach to finite-sample inference and nonstandard asymptotics
• Useful invariance results for generalized regression models
• Robust regression: Asymptotics, conjectures and Monte Carlo
• Robust tests for normality of errors in regression models
• Least Median of Squares Regression
• GENERAL TRIMMED ESTIMATION: ROBUST APPROACH TO NONLINEAR AND LIMITED DEPENDENT VARIABLE MODELS
• Some Measurability Results for Extrema of Random Functions Over Random Sets
• One-Step Huber Estimates in the Linear Model
• Regression Quantiles
• Estimating Regression Coefficients by Minimizing the Dispersion of the Residuals
• Estimates of Parameters of a Censored Regression Sample
• A Test of Goodness of Fit

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