文章基本信息

标题：Nonparametric estimation of the residual entropy function with censored dependent data
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作者：G. Rajesh ; E. I. Abdul-Sathar ; R. Maya 等
期刊名称：Brazilian Journal of Probability and Statistics
印刷版ISSN：0103-0752
出版年度：2015
卷号：29
期号：4
页码：866-877
DOI：10.1214/14-BJPS250
语种：English
出版社：Brazilian Statistical Association
摘要：The residual entropy function introduced by Ebrahimi [Sankhyā A 58 (1996) 48–56], is viewed as a dynamic measure of uncertainty. This measure finds applications in modeling and analysis of life time data. In the present work, we propose nonparametric estimators for the residual entropy function based on censored data. Asymptotic properties of the estimator are established under suitable regularity conditions. Monte Carlo simulation studies are carried out to compare the performance of the estimators using the mean-squared error. The methods are illustrated using two real data sets.