Original title: A Bootstrap Comparison of Robust Regression Estimators
Authors: Kalina, Jan ; Janáček, Patrik
Document type: Papers
Conference/Event: MME 2022: International Conference on Mathematical Methods in Economics /40./, Jihlava (CZ), 20220907
Year: 2022
Language: eng
Abstract: 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.
Keywords: bootstrap hypothesis testing; linear regression; nonparametric bootstrap; robust estimation
Project no.: GA21-05325S (CEP)
Funding provider: GA ČR
Host item entry: Mathematical Methods in Economics 2022: Proceedings, ISBN 978-80-88064-62-6

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: https://library.utia.cas.cz/separaty/2023/SI/kalina-0583572.pdf
Original record: https://hdl.handle.net/11104/0351580

Permalink: http://www.nusl.cz/ntk/nusl-541552


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Conference materials > Papers