On weighted and locally polynomial directional quantile regression

0474696 - ÚTIA 2018 RIV DE eng J - Článek v odborném periodiku
Boček, Pavel - Šiman, Miroslav
On weighted and locally polynomial directional quantile regression.
Computational Statistics. Roč. 32, č. 3 (2017), s. 929-946. ISSN 0943-4062. E-ISSN 1613-9658
Grant CEP: GA ČR GA14-07234S
Institucionální podpora: RVO:67985556
Klíčová slova: Quantile regression * Nonparametric regression * Nonparametric regression
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impakt faktor: 0.828, rok: 2017
http://library.utia.cas.cz/separaty/2017/SI/bocek-0458380.pdf

The article deals with certain quantile regression methods for vector responses. In particular, it describes weighted and locally polynomial extensions to the projectional quantile regression, discusses their properties, addresses their computational side, compares their outcome with recent analogous generalizations of the competing multiple-output directional quantile regression, demonstrates a link between the two competing methodologies, complements the results already available in the literature, illustrates the concepts with a few simulated and insightful examples illustrating some of their features, and shows their application to a real financial data set, namely to Forex 1M exchange rates. The real-data example strongly indicates that the presented methods might have a huge impact on the analysis of multivariate time series consisting of two to four dimensional observations.
Trvalý link: http://hdl.handle.net/11104/0271770