Academic Journal
Relative error prediction: Strong uniform consistency for censoring time series model
| العنوان: | Relative error prediction: Strong uniform consistency for censoring time series model |
|---|---|
| المؤلفون: | Bouhadjera, Feriel, Elias, Ould Saïd, Mohamed Riad, Remita |
| المساهمون: | Laboratoire de Mathématiques Pures et Appliquées Joseph Liouville (LMPA), Université du Littoral Côte d'Opale (ULCO), Laboratoire de Probabilités et Statistique - LaPS (Annaba, Algérie), Université Badji Mokhtar - Annaba (ALGERIA) |
| المصدر: | ISSN: 0361-0926. |
| بيانات النشر: | HAL CCSD Taylor & Francis |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Censored data, Kernel estimate, regression function, relative error, strong mixing, uniform almost sure consistency, Mathematics Subject Classification: 62G05, 62G08, 62G35, 62N02, [STAT]Statistics [stat], [MATH]Mathematics [math], stat |
| الوصف: | International audience ; This article considers an adaptive method based on the relative error criteria to estimate the regression operator by a kernel smoothing. It is assumed that the variable of interest is subject to random right censoring and that the observations are from a stationary α-mixing process. The uniform almost sure consistency over a compact set with rate where we highlighted the covariance term is established. The simulation study indicates that the proposed approach has better performance in the presence of high level censoring and outliers in data to an existing classical method based on the least squares. An experiment prediction shows the quality of the relative error predictor |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| Relation: | https://hal.archives-ouvertes.fr/hal-03771999 |
| الاتاحة: | https://hal.archives-ouvertes.fr/hal-03771999 |
| Rights: | undefined |
| رقم الانضمام: | edsbas.1CD1D2F4 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |