Název: Implicitly weighted robust estimation of quantiles in linear regression
Autoři: Kalina, Jan ; Vidnerová, Petra
Typ dokumentu: Příspěvky z konference
Konference/Akce: MME 2019: International Conference on Mathematical Methods in Economics /37./, České Budějovice (CZ), 20190911
Rok: 2019
Jazyk: eng
Abstrakt: Estimation of quantiles represents a very important task in econometric regression modeling, while the standard regression quantiles machinery is well developed as well as popular with a large number of econometric applications. Although regression quantiles are commonly known as robust tools, they are vulnerable to the presence of leverage points in the data. We propose here a novel approach for the linear regression based on a specific version of the least weighted squares estimator, together with an additional estimator based only on observations between two different novel quantiles. The new methods are conceptually simple and comprehensible. Without the ambition to derive theoretical properties of the novel methods, numerical computations reveal them to perform comparably to standard regression quantiles, if the data are not contaminated by outliers. Moreover, the new methods seem much more robust on a simulated dataset with severe leverage points.
Klíčová slova: leverage points; outliers; regression quantiles; robust regression
Číslo projektu: GA19-05704S (CEP), GA18-23827S (CEP)
Poskytovatel projektu: GA ČR, GA ČR
Zdrojový dokument: Conference Proceedings. 37th International Conference on Mathematical Methods in Economics 2019, ISBN 978-80-7394-760-6

Instituce: Ústav informatiky AV ČR (web)
Informace o dostupnosti dokumentu: Dokument je dostupný na externích webových stránkách.
Externí umístění souboru: https://mme2019.ef.jcu.cz/files/conference_proceedings.pdf
Původní záznam: http://hdl.handle.net/11104/0300322

Trvalý odkaz NUŠL: http://www.nusl.cz/ntk/nusl-403665


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