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Conference Paper (international conference)

How to down-weight observations in robust regression: A metalearning study

Kalina Jan, Pitra Z.

: Mathematical Methods in Economics 2018. Conference Proceedings, p. 204-209 , Eds: Váchová L., Kratochvíl V.

: MME 2018. International Conference Mathematical Methods in Economics /36./, (Jindřichův Hradec, CZ, 20180912)

: GA17-07384S, GA ČR, GA17-01251S, GA ČR

: metalearning, robust statistics, linear regression, outliers

: http://library.utia.cas.cz/separaty/2019/SI/kalina-0506986.pdf

(eng): 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.

: BB

: 10103