Empirical regression quantile processes

Jana Jurečková; Jan Picek; Martin Schindler

Applications of Mathematics (2020)

  • Volume: 65, Issue: 3, page 257-269
  • ISSN: 0862-7940

Abstract

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We address the problem of estimating quantile-based statistical functionals, when the measured or controlled entities depend on exogenous variables which are not under our control. As a suitable tool we propose the empirical process of the average regression quantiles. It partially masks the effect of covariates and has other properties convenient for applications, e.g. for coherent risk measures of various types in the situations with covariates.

How to cite

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Jurečková, Jana, Picek, Jan, and Schindler, Martin. "Empirical regression quantile processes." Applications of Mathematics 65.3 (2020): 257-269. <http://eudml.org/doc/297244>.

@article{Jurečková2020,
abstract = {We address the problem of estimating quantile-based statistical functionals, when the measured or controlled entities depend on exogenous variables which are not under our control. As a suitable tool we propose the empirical process of the average regression quantiles. It partially masks the effect of covariates and has other properties convenient for applications, e.g. for coherent risk measures of various types in the situations with covariates.},
author = {Jurečková, Jana, Picek, Jan, Schindler, Martin},
journal = {Applications of Mathematics},
keywords = {averaged regression quantile; one-step regression quantile; $R$-estimator; functionals of the quantile process},
language = {eng},
number = {3},
pages = {257-269},
publisher = {Institute of Mathematics, Academy of Sciences of the Czech Republic},
title = {Empirical regression quantile processes},
url = {http://eudml.org/doc/297244},
volume = {65},
year = {2020},
}

TY - JOUR
AU - Jurečková, Jana
AU - Picek, Jan
AU - Schindler, Martin
TI - Empirical regression quantile processes
JO - Applications of Mathematics
PY - 2020
PB - Institute of Mathematics, Academy of Sciences of the Czech Republic
VL - 65
IS - 3
SP - 257
EP - 269
AB - We address the problem of estimating quantile-based statistical functionals, when the measured or controlled entities depend on exogenous variables which are not under our control. As a suitable tool we propose the empirical process of the average regression quantiles. It partially masks the effect of covariates and has other properties convenient for applications, e.g. for coherent risk measures of various types in the situations with covariates.
LA - eng
KW - averaged regression quantile; one-step regression quantile; $R$-estimator; functionals of the quantile process
UR - http://eudml.org/doc/297244
ER -

References

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