0564518 20240406001922.620221125235959.9 000936355000066 7 s. E cav_un_epca*0564517978-80-88064-62-6161-167JihlavaCollege of Polytechnics Jihlava2022VojáčkováH. linear regression robust estimation nonparametric bootstrap bootstrap hypothesis testing cav_un_auth*0263018 Kalina Jan UIVT-O Oddělení strojového učení Department of Machine Learning Department of Machine Learning Ústav informatiky AV ČR, v. v. i. cav_un_auth*0448197 Janáček Patrik UTIA-B Stochastická informatika Department of Stochastic Informatics SI SI CZ Ústav teorie informace a automatizace AV ČR, v. v. i. https://mme2022.vspj.cz/download/proceedings-4.pdf GA21-05325S GA ČR cav_un_auth*0409039 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. cav_un_auth*0440547 MME 2022: International Conference on Mathematical Methods in Economics /40./ 20220907 20220909 Jihlava CZ 10000 10100 10103 2023 UTIA-B 10000 10100 10103 4 O 4o 20231122150950.0 RVO:67985807 RVO:67985556 https://hdl.handle.net/11104/0336179 S n.a. Proceedings Paper Economics|Mathematics Interdisciplinary Applications|Social Sciences Mathematical Methods 2022 Soubory v repozitáři: 0564518-aonl.pdf SCOPUS PUBMED 000936355000066 WOS cav_un_epca*0564517 Mathematical Methods in Economics 2022: Proceedings College of Polytechnics Jihlava 2022 Jihlava 161 167 978-80-88064-62-6 Vojáčková H. 340