0532048 20240103224404.720200908235959.9 85087049309 000544260100004 10.21136/AM.2020.0295-19 13 s. P cav_un_epca*02906540862-7940653 (2020)257-269Springer averaged regression quantile R-estimator functionals of the quantile process cav_un_auth*0368969 33,35 Jurečková Jana UTIA-B Stochastická informatika Department of Stochastic Informatics SI SI CZ S Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0019770 Picek J. CZ cav_un_auth*0293529 Schindler M. CZ http://library.utia.cas.cz/separaty/2020/SI/jureckova-0532048.pdf https://link.springer.com/article/10.21136/AM.2020.0295-19 cav_un_auth*0370462 GA18-01137S GA ČR CZ 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. WOS BA 10000 10100 10103 2021 3 RVO:67985556 http://hdl.handle.net/11104/0310669 cav_un_auth*0295064 Technická univerzita v Liberci TUL S 3+4 Article|Proceedings Paper Mathematics Applied A MATHEMATICS.APPLIED 0.815 0.056 11.7 0.00049 0.283 467 33 0.237 21.3 0.7 84 Q4 0.866 54 Q4 3.216 23.2 Q4 Q3 0.43 Q4 23.208 2020 85087049309 SCOPUS 000544260100004 WOS cav_un_epca*0290654 Applications of Mathematics 0862-7940 1572-9109 Roč. 65 č. 3 2020 257 269 Springer