0506986 20240103222332.920190729235959.9 000507455300036 How to down-weight observations in robust regression: A metalearning study 6 s. P cav_un_epca*0493804978-80-7378-371-6Mathematical Methods in Economics 2018. Conference Proceedings204-209PragueMatfyzPress2018VáchováL.KratochvílV. metalearning robust statistics linear regression outliers cav_un_auth*0345793 Kalina Jan UTIA-B Stochastická informatika Department of Stochastic Informatics SI SI Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0319208 Pitra Z. CZ http://library.utia.cas.cz/separaty/2019/SI/kalina-0506986.pdf cav_un_auth*0345381 GA17-07384S GA ČR cav_un_auth*0345802 GA17-01251S GA ČR Metalearning is becoming an increasingly important methodology for extracting knowledge from a data base of available training data sets to a new (independent) data set. The concept of metalearning is becoming popular in statistical learning and there is an increasing number of metalearning applications also in the analysis of economic data sets. Still, not much attention has been paid to its limitations and disadvantages. For this purpose, we use various linear regression estimators (including highly robust ones) over a set of 30 data sets with economic background and perform a metalearning study over them as well as over the same data sets after an artificial contamination. cav_un_auth*0364490 MME 2018. International Conference Mathematical Methods in Economics /36./ 20180912 20180914 Jindřichův Hradec CZ BB 10000 10100 10103 2020 UIVT-O 10000 10100 10103 PR UIVT-O BB RVO:67985556 RVO:67985807 http://hdl.handle.net/11104/0298101 S 3+4 Proceedings Paper Economics|Mathematics Interdisciplinary Applications|Social Sciences Mathematical Methods 3+4 Proceedings Paper Economics|Mathematics Interdisciplinary Applications|Social Sciences Mathematical Methods 3+4 Proceedings Paper Economics|Mathematics Interdisciplinary Applications|Social Sciences Mathematical Methods 2018 SCOPUS PUBMED 000507455300036 WOS cav_un_epca*0493804 Mathematical Methods in Economics 2018. Conference Proceedings MatfyzPress 2018 Prague 204 209 978-80-7378-371-6 340 Váchová L. 340 Kratochvíl V.