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Normality testing after outlier removal
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DOI：10.1016/j.ecosta.2023.06.001.png)
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Abstract
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The cumulant based normality test after outlier removal is analyzed. It is shown that the standard least squares normalizations can be misleading in this context. The sample cumulants should be standardized according to the truncation imposed at the removal stage and the estimation method being used. New standardizations that lead to chi-squared inference are derived. (c) 2023 The Author(s). Published by Elsevier B.V. on behalf of EcoSta Econometrics and Statistics. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Keywords:
Least Trimmed Squares Estimator
Robustified Least Squares Estimator
Truncated normality
Misspecification testing
Asymptotic theory
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