Název: A Bootstrap Comparison of Robust Regression Estimators
Autoři: Kalina, Jan ; Janáček, Patrik
Typ dokumentu: Příspěvky z konference
Konference/Akce: MME 2022: International Conference on Mathematical Methods in Economics /40./, Jihlava (CZ), 20220907
Rok: 2022
Jazyk: eng
Abstrakt: The ordinary least squares estimator in linear regression is well known to be highly vulnerable to the presence of outliers in the data and available robust statistical estimators represent more preferable alternatives. It has been repeatedly recommended to use the least squares together with a robust estimator, where the latter is understood as a diagnostic tool for the former. In other words, only if the robust estimator yields a very different result, the user should investigate the dataset closer and search for explanations. For this purpose, a hypothesis test of equality of the means of two alternative linear regression estimators is proposed here based on nonparametric bootstrap. The performance of the test is presented on three real economic datasets with small samples. Robust estimates turn out not to be significantly different from non-robust estimates in the selected datasets. Still, robust estimation is beneficial in these datasets and the experiments illustrate one of possible ways of exploiting the bootstrap methodology in regression modeling. The bootstrap test could be easily extended to nonlinear regression models.
Klíčová slova: bootstrap hypothesis testing; linear regression; nonparametric bootstrap; robust estimation
Číslo projektu: GA21-05325S (CEP)
Poskytovatel projektu: GA ČR
Zdrojový dokument: Mathematical Methods in Economics 2022: Proceedings, ISBN 978-80-88064-62-6

Instituce: Ústav informatiky AV ČR (web)
Informace o dostupnosti dokumentu: Dokument je dostupný na externích webových stránkách.
Externí umístění souboru: https://mme2022.vspj.cz/download/proceedings-4.pdf
Původní záznam: https://hdl.handle.net/11104/0336179

Trvalý odkaz NUŠL: http://www.nusl.cz/ntk/nusl-511783


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