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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| Published in | Journal of the Korean Statistical Society Vol. 54; no. 1; pp. 220 - 247 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Singapore
Springer Nature Singapore
01.03.2025
한국통계학회 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1226-3192 2005-2863 |
| DOI | 10.1007/s42952-024-00293-0 |
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| Abstract | 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. |
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| AbstractList | 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. KCI Citation Count: 0 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. |
| Author | Sarra, Leulmi |
| Author_xml | – sequence: 1 givenname: Leulmi surname: Sarra fullname: Sarra, Leulmi email: sara.leulmi@umc.edu.dz, math17sara@yahoo.fr organization: Laboratoire LAMASD, département de Mathématiques, Université frères Mentouri Constantine 1 |
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| Cites_doi | 10.1515/ms-2017-0443 10.1111/j.1467-842X.2007.00480.x 10.1016/S0246-0203(99)00112-0 10.1080/10485252.2015.1114112 10.1080/10485252.2018.1546386 10.1016/j.spl.2012.06.026 10.1016/j.jspi.2009.07.019 10.1016/j.spl.2014.10.005 10.1016/0304-405X(93)90023-5 10.1016/j.spl.2018.09.009 10.1007/s13171-021-00276-x 10.1016/j.spl.2013.04.017 10.1016/j.spl.2015.07.017 10.1080/01621459.1958.10501452 |
| ContentType | Journal Article |
| Copyright | Korean Statistical Society 2024 Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| Copyright_xml | – notice: Korean Statistical Society 2024 Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Keywords | Twice censored data 62M10 62P30 62N01 Functional data Asymptotic normality Regression function Kernel estimation 62G20 |
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| Title | Asymptotic normality of kernel functional regression estimator based upon twice censored data |
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