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A Bootstrap Comparison of Robust Regression Estimators
- 1.0583572 - ÚTIA 2024 RIV CZ eng C - Conference Paper (international conference)
Kalina, Jan - Janáček, Patrik
A Bootstrap Comparison of Robust Regression Estimators.
Mathematical Methods in Economics 2022: Proceedings. Jihlava: College of Polytechnics Jihlava, 2022 - (Vojáčková, H.), s. 161-167. ISBN 978-80-88064-62-6.
[MME 2022: International Conference on Mathematical Methods in Economics /40./. Jihlava (CZ), 07.09.2022-09.09.2022]
R&D Projects: GA ČR GA21-05325S
Institutional support: RVO:67985556
Keywords : linear regression * robust estimation * nonparametric bootstrap * bootstrap hypothesis testing
OECD category: Statistics and probability
http://library.utia.cz/separaty/2023/SI/kalina-0583572.pdf
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.
Permanent Link: https://hdl.handle.net/11104/0351580
Number of the records: 1