A Note on Nonparametric Estimation of Conditional Hazard Quantile Function

DOI

10.2991/jrarc.2017.7.3.1How to use a DOI?

Keywords

Asymptotic normality, conditional hazard quantile function, functional data, kernel smoothing, nonparametric estimator.

Abstract

In this paper, we study an kernel estimator of the conditional hazard quantile function (CHQF) of a scalar response variable Y given a random variable (rv) X taking values in a semi-metric space and using the proposed estimator based of the kernel smoothing method. The almost complete consistency and the asymptotic normality of this estimate are obtained when the sample is an independante sequence.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - El Hadj Hamel
AU  - Nadia Kadiri
AU  - Abbes Rabhi
PY  - 2017
DA  - 2017/10/02
TI  - A Note on Nonparametric Estimation of Conditional Hazard Quantile Function
JO  - Journal of Risk Analysis and Crisis Response
SP  - 101
EP  - 107
VL  - 7
IS  - 3
SN  - 2210-8505
UR  - https://doi.org/10.2991/jrarc.2017.7.3.1
DO  - 10.2991/jrarc.2017.7.3.1
ID  - Hamel2017
ER  -