<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The main objective of this paper was to estimate non-parametrically the quantiles of a conditional distribution based on the single-index model in the censorship model when the sample is considered as independent and identically distributed (i.i.d.) random variables. First of all, a kernel type estimator for the conditional cumulative distribution function (<italic>cond-cdf</italic>) is introduced. Then the paper gives an estimation of the quantiles by inverting this estimated <italic>cond-cdf</italic>, the asymptotic properties are stated when the observations are linked with a single-index structure. Finally, a simulation study was carried out to evaluate the performance of this estimate.</p>
</abstract>

The main objective of this paper was to estimate non-parametrically the quantiles of a conditional distribution based on the single-index model in the censorship model when the sample is considered as independent and identically distributed (i.i.d.) random variables. First of all, a kernel type estimator for the conditional cumulative distribution function (cond-cdf) is introduced. Then the paper gives an estimation of the quantiles by inverting this estimated cond-cdf, the asymptotic properties are stated when the observations are linked with a single-index structure. Finally, a simulation study was carried out to evaluate the performance of this estimate.

Single Functional Index Quantile Regression for Independent Functional Data Under Right-Censoring

University Djillali Liabes of Sidi Bel Abbes

Department of Mathematics and Computer Science

Econometrics

This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License.

The main objective of this paper was to estimate non-parametrically the quantiles of a conditional distribution based on the single-index model in the...

Single Functional Index Quantile Regression for Independent Functional Data Under Right-Censoring

Publié en ligne: 14 juin 2022

Pages: 31 - 62

DOI: https://doi.org/10.15611/eada.2022.1.03

Mots clés
censored data, functional data, kernel estimator, normality, non-parametric estimation, small ball probability

© 2022 Mohamed Mehdi Hamri et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License.

Single Functional Index Quantile Regression for Independent Functional Data Under Right-Censoring

Publié en ligne: 14 juin 2022

Pages: 31 - 62

DOI: https://doi.org/10.15611/eada.2022.1.03

Mots cléscensored data, functional data, kernel estimator, normality, non-parametric estimation, small ball probability

© 2022 Mohamed Mehdi Hamri et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License.

Mots clés
censored data, functional data, kernel estimator, normality, non-parametric estimation, small ball probability