Conditional Density Kernel Estimation Under Random Censorship for Functional Weak Dependence Data
The primary objective of this research is to investigate the asymptotic properties of the conditional density nonparametric estimator. The main areas of focus are the estimator’s consistency (with rates), including those involving censored data and quasi-associated dependent variables, as well as it...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/jom/2159604 |
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| _version_ | 1850036658548768768 |
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| author | Hamza Daoudi Abderrahmane Belguerna Zouaoui Chikr Elmezouar Fatimah Alshahrani |
| author_facet | Hamza Daoudi Abderrahmane Belguerna Zouaoui Chikr Elmezouar Fatimah Alshahrani |
| author_sort | Hamza Daoudi |
| collection | DOAJ |
| description | The primary objective of this research is to investigate the asymptotic properties of the conditional density nonparametric estimator. The main areas of focus are the estimator’s consistency (with rates), including those involving censored data and quasi-associated dependent variables, as well as its performance when the covariate is functional in nature. For this model, we establish the almost complete pointwise convergence of the conditional density estimate. The findings from this research contribute to the theoretical foundations of nonparametric density estimation, with direct implications for data analysis and decision-making in various fields, such as biomedical research, finance, and social sciences. To empirically examine the practical implications of the established asymptotic properties, we conducted a series of simulation experiments. These numerical studies allow us to investigate the finite-sample performance of the conditional density nonparametric estimator and validate the theoretical findings. |
| format | Article |
| id | doaj-art-fb665c30d4e44c2596c44ec52a8aba39 |
| institution | DOAJ |
| issn | 2314-4785 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-fb665c30d4e44c2596c44ec52a8aba392025-08-20T02:57:05ZengWileyJournal of Mathematics2314-47852025-01-01202510.1155/jom/2159604Conditional Density Kernel Estimation Under Random Censorship for Functional Weak Dependence DataHamza Daoudi0Abderrahmane Belguerna1Zouaoui Chikr Elmezouar2Fatimah Alshahrani3Department of Electrical EngineeringLaboratory of MathematicsDepartment of MathematicsDepartment of Mathematical SciencesThe primary objective of this research is to investigate the asymptotic properties of the conditional density nonparametric estimator. The main areas of focus are the estimator’s consistency (with rates), including those involving censored data and quasi-associated dependent variables, as well as its performance when the covariate is functional in nature. For this model, we establish the almost complete pointwise convergence of the conditional density estimate. The findings from this research contribute to the theoretical foundations of nonparametric density estimation, with direct implications for data analysis and decision-making in various fields, such as biomedical research, finance, and social sciences. To empirically examine the practical implications of the established asymptotic properties, we conducted a series of simulation experiments. These numerical studies allow us to investigate the finite-sample performance of the conditional density nonparametric estimator and validate the theoretical findings.http://dx.doi.org/10.1155/jom/2159604 |
| spellingShingle | Hamza Daoudi Abderrahmane Belguerna Zouaoui Chikr Elmezouar Fatimah Alshahrani Conditional Density Kernel Estimation Under Random Censorship for Functional Weak Dependence Data Journal of Mathematics |
| title | Conditional Density Kernel Estimation Under Random Censorship for Functional Weak Dependence Data |
| title_full | Conditional Density Kernel Estimation Under Random Censorship for Functional Weak Dependence Data |
| title_fullStr | Conditional Density Kernel Estimation Under Random Censorship for Functional Weak Dependence Data |
| title_full_unstemmed | Conditional Density Kernel Estimation Under Random Censorship for Functional Weak Dependence Data |
| title_short | Conditional Density Kernel Estimation Under Random Censorship for Functional Weak Dependence Data |
| title_sort | conditional density kernel estimation under random censorship for functional weak dependence data |
| url | http://dx.doi.org/10.1155/jom/2159604 |
| work_keys_str_mv | AT hamzadaoudi conditionaldensitykernelestimationunderrandomcensorshipforfunctionalweakdependencedata AT abderrahmanebelguerna conditionaldensitykernelestimationunderrandomcensorshipforfunctionalweakdependencedata AT zouaouichikrelmezouar conditionaldensitykernelestimationunderrandomcensorshipforfunctionalweakdependencedata AT fatimahalshahrani conditionaldensitykernelestimationunderrandomcensorshipforfunctionalweakdependencedata |