A non-parametric estimation of the conditional quantile for truncated and functional data
type: Item
instance of: scholarly article
title: A non-parametric estimation of the conditional quantile for truncated and functional data
zbMATH Open document ID: 1486.62097
DOI: 10.1504/IJMOR.2022.120318
author: Halima Boudada
published in: International Journal of Mathematics in Operational Research
publication date: 2022-03-14T00:00:00Z
review text: Summary: In this paper, we propose a local linear estimator for the conditional distribution function in the case where the real response variable is subject to left-truncation by another random variable (r.v.) and the covariate is of functional type. Under regular assumptions, both of the pointwise and the uniform almost sure convergences, of the proposed estimator, are established. Then, we deduce the uniform almost sure convergence of the obtained conditional quantile estimator. A simulation study is used to illustrate the performance of our estimator with respect to the kernel method.
Mathematics Subject Classification ID: 62G08
Mathematics Subject Classification ID: 62G05
Mathematics Subject Classification ID: 62G20
Mathematics Subject Classification ID: 62R10
zbMATH DE Number: 7488839
zbMATH Keywords: truncation
zbMATH Keywords: functional-type covariate
zbMATH Keywords: local linear method
zbMATH Keywords: conditional quantile function
zbMATH Keywords: rate of almost-sure convergence
zbMATH Keywords: simulation
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 7488839