Original title: How to down-weight observations in robust regression: A metalearning study
Authors: Kalina, Jan ; Pitra, Z.
Document type: Papers
Conference/Event: MME 2018. International Conference Mathematical Methods in Economics /36./, Jindřichův Hradec (CZ), 20180912
Year: 2018
Language: eng
Abstract: 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.
Keywords: linear regression; metalearning; outliers; robust statistics
Project no.: GA17-07384S (CEP), GA17-01251S (CEP)
Funding provider: GA ČR, GA ČR
Host item entry: Mathematical Methods in Economics 2018. Conference Proceedings, ISBN 978-80-7378-371-6

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2019/SI/kalina-0506986.pdf
Original record: http://hdl.handle.net/11104/0298101

Permalink: http://www.nusl.cz/ntk/nusl-399157


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