Brazilian Journal of Probability and Statistics

Nonparametric estimation of the residual entropy function with censored dependent data

G. Rajesh, E. I. Abdul-Sathar, R. Maya, and K. R. Muraleedharan Nair

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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.

Article information

Braz. J. Probab. Stat., Volume 29, Number 4 (2015), 866-877.

Received: July 2013
Accepted: May 2014
First available in Project Euclid: 17 September 2015

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Zentralblatt MATH identifier

Residual entropy function kernel estimate $\alpha$-mixing residual life


Rajesh, G.; Abdul-Sathar, E. I.; Maya, R.; Muraleedharan Nair, K. R. Nonparametric estimation of the residual entropy function with censored dependent data. Braz. J. Probab. Stat. 29 (2015), no. 4, 866--877. doi:10.1214/14-BJPS250.

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