Asymptotic normality of kernel functional regression estimator based upon twice censored data

In this paper, we introduce a new kernel functional regression estimator when the random response variable is subject to twice censoring. Then, we establish the asymptotic normality of our estimator and we deduce the asymptotic confidence interval of the regression function. To enhance our theoretic...

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Bibliographic Details
Published inJournal of the Korean Statistical Society Vol. 54; no. 1; pp. 220 - 247
Main Author Sarra, Leulmi
Format Journal Article
LanguageEnglish
Published Singapore Springer Nature Singapore 01.03.2025
한국통계학회
Subjects
Applied Statistics
Bayesian Inference
Mathematics and Statistics
Research Article
Statistical Theory and Methods
Statistics
Statistics and Computing/Statistics Programs
통계학
Twice censored data
62M10
62P30
62N01
Functional data
Asymptotic normality
Regression function
Kernel estimation
62G20
Online AccessGet full text
ISSN1226-3192
2005-2863
DOI10.1007/s42952-024-00293-0

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Summary:In this paper, we introduce a new kernel functional regression estimator when the random response variable is subject to twice censoring. Then, we establish the asymptotic normality of our estimator and we deduce the asymptotic confidence interval of the regression function. To enhance our theoretical results, the performance and the asymptotic Gaussian behavior of our estimator are highlighted through a simulation study and an application to real data.
ISSN:1226-3192
2005-2863
DOI:10.1007/s42952-024-00293-0