Global nonparametric estimation of conditional quantile functions and their derivatives

Probal Chaudhuri

Journal of Multivariate Analysis, 1991, vol. 39, issue 2, 246-269

Abstract: Let (X, Y) be a random vector such that X is d-dimensional, Y is real valued, and [theta](X) is the conditional [alpha]th quantile of Y given X, where [alpha] is a fixed number such that 0 0, and set r = (p - m)/(2p + d), where m is a nonnegative integer smaller than p. Let T([theta]) denote a derivative of [theta] of order m. It is proved that there exists estimate of T([theta]), based on a set of i.i.d. observations (X1, Y1), ..., (Xn, Yn), that achieves the optimal nonparametric rate of convergence n-r in Lq-norms (1

Keywords: regression; quantiles; nonparametric; estimates; bin; smoothers; optimal; rates; of; convergence (search for similar items in EconPapers)
Date: 1991
References: Add references at CitEc
Citations: View citations in EconPapers (48)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0047-259X(91)90100-G
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:39:y:1991:i:2:p:246-269

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().