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Empirical regression quantile process
- 1.0532048 - ÚTIA 2021 RIV CZ eng J - Journal Article
Jurečková, Jana - Picek, J. - Schindler, M.
Empirical regression quantile process.
Applications of Mathematics. Roč. 65, č. 3 (2020), s. 257-269. ISSN 0862-7940. E-ISSN 1572-9109
Grant - others:GA ČR(CZ) GA18-01137S
Institutional support: RVO:67985556
Keywords : averaged regression quantile * R-estimator * functionals of the quantile process
OECD category: Statistics and probability
Impact factor: 0.881, year: 2020
Method of publishing: Open access
http://library.utia.cas.cz/separaty/2020/SI/jureckova-0532048.pdf https://link.springer.com/article/10.21136/AM.2020.0295-19
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.
Permanent Link: http://hdl.handle.net/11104/0310669
Number of the records: 1