Local linear estimation of the conditional mode under left truncation for functional regressors
Kybernetika (2023)
- Volume: 59, Issue: 4, page 548-574
- ISSN: 0023-5954
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topBoudada, Halima, and Leulmi, Sarra. "Local linear estimation of the conditional mode under left truncation for functional regressors." Kybernetika 59.4 (2023): 548-574. <http://eudml.org/doc/299407>.
@article{Boudada2023,
abstract = {In this work, we introduce a local linear estimator of the conditional mode for a random real response variable which is subject to left-truncation by another random variable where the covariate takes values in an infinite dimensional space. We first establish both of pointwise and uniform almost sure convergences, with rates, of the conditional density estimator. Then, we deduce the strong consistency of the obtained conditional mode estimator. We finally illustrate the outperformance of our method with respect to the kernel one through a simulation study for a finite sample with different rates of truncation and sizes.},
author = {Boudada, Halima, Leulmi, Sarra},
journal = {Kybernetika},
keywords = {functional regressors; left truncation model; conditional mode; almost sure convergence; local linear estimator},
language = {eng},
number = {4},
pages = {548-574},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Local linear estimation of the conditional mode under left truncation for functional regressors},
url = {http://eudml.org/doc/299407},
volume = {59},
year = {2023},
}
TY - JOUR
AU - Boudada, Halima
AU - Leulmi, Sarra
TI - Local linear estimation of the conditional mode under left truncation for functional regressors
JO - Kybernetika
PY - 2023
PB - Institute of Information Theory and Automation AS CR
VL - 59
IS - 4
SP - 548
EP - 574
AB - In this work, we introduce a local linear estimator of the conditional mode for a random real response variable which is subject to left-truncation by another random variable where the covariate takes values in an infinite dimensional space. We first establish both of pointwise and uniform almost sure convergences, with rates, of the conditional density estimator. Then, we deduce the strong consistency of the obtained conditional mode estimator. We finally illustrate the outperformance of our method with respect to the kernel one through a simulation study for a finite sample with different rates of truncation and sizes.
LA - eng
KW - functional regressors; left truncation model; conditional mode; almost sure convergence; local linear estimator
UR - http://eudml.org/doc/299407
ER -
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