Monte Carlo power comparison of seven most commonly used heteroscedasticity tests

DOI10.1080/03610918.2019.1692031OpenAlexW2990957497WikidataQ126775361 ScholiaQ126775361MaRDI QIDQ5082956

Stanislaus S. Uyanto

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2019.1692031

zbMATH Keywords

ordinary least squaresresidualsregression diagnostichomocedasticity

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• R

Cites Work

• Unnamed Item
• A Simple Test for Heteroscedasticity and Random Coefficient Variation
• Diagnostics for heteroscedasticity in regression
• Simulation-based finite-sample tests for heteroskedasticity and ARCH effects
• A Test for Heteroscedasticity Based on Ordinary Least Squares Residuals
• A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
• A study of several new and existing tests for heteroscedasticity in the general linear model
• Testing for multiplicative heteroskedasticity
• A comparison of the power of some tests for heteroskedasticity in the general linear model
• Estimating Regression Models with Multiplicative Heteroscedasticity
• A historical note on the method of least squares
• SOME THEOREMS IN LEAST SQUARES

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