Gamma Kernel Estimators for Density and Hazard Rate of Right-Censored Data
Joint Authors
El Ghouch, A.
Mesfioui, Mhamed
Bouezmarni, T.
Source
Journal of Probability and Statistics
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-06-16
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
The nonparametric estimation for the density and hazard rate functions for right-censored data using the kernel smoothing techniques is considered.
The “classical” fixed symmetric kernel type estimator of these functions performs well in the interior region, but it suffers from the problem of bias in the boundary region.
Here, we propose new estimators based on the gamma kernels for the density and the hazard rate functions.
The estimators are free of bias and achieve the optimal rate of convergence in terms of integrated mean squared error.
The mean integrated squared error, the asymptotic normality, and the law of iterated logarithm are studied.
A comparison of gamma estimators with the local linear estimator for the density function and with hazard rate estimator proposed by Müller and Wang (1994), which are free from boundary bias, is investigated by simulations.
American Psychological Association (APA)
Bouezmarni, T.& El Ghouch, A.& Mesfioui, Mhamed. 2011. Gamma Kernel Estimators for Density and Hazard Rate of Right-Censored Data. Journal of Probability and Statistics،Vol. 2011, no. 2011, pp.1-16.
https://search.emarefa.net/detail/BIM-509675
Modern Language Association (MLA)
Bouezmarni, T.…[et al.]. Gamma Kernel Estimators for Density and Hazard Rate of Right-Censored Data. Journal of Probability and Statistics No. 2011 (2011), pp.1-16.
https://search.emarefa.net/detail/BIM-509675
American Medical Association (AMA)
Bouezmarni, T.& El Ghouch, A.& Mesfioui, Mhamed. Gamma Kernel Estimators for Density and Hazard Rate of Right-Censored Data. Journal of Probability and Statistics. 2011. Vol. 2011, no. 2011, pp.1-16.
https://search.emarefa.net/detail/BIM-509675
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-509675