kernel conditional quantile estimator under left truncation for functional regressors

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ID: 153370
2016
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Abstract
Let \(Y\) be a random real response which is subject to left-truncation by another random variable \(T\). In this paper, we study the kernel conditional quantile estimation when the covariable \(X\) takes values in an infinite-dimensional space. A kernel conditional quantile estimator is given under some regularity conditions, among which in the small-ball probability, its strong uniform almost sure convergence rate is established. Some special cases have been studied to show how our work extends some results given in the literature. Simulations are drawn to lend further support to our theoretical results and assess the behavior of the estimator for finite samples with different rates of truncation and sizes.
Reference Key
helal2016opusculakernel Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Nacéra Helal;Elias Ould Saïd
Journal zhonghua yi xue za zhi
Year 2016
DOI
http://dx.doi.org/10.7494/OpMath.2016.36.1.25
URL
http://www.opuscula.agh.edu.pl/vol36/1/art/opuscula_math_3602.pdf
Keywords
quantitative methods

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