A Comparative Study of Traditional and Kullback-Leibler Divergence of Survival Functions Estimators for the Parameter of Lindley Distribution

A new point estimation method based on Kullback-Leibler divergence of survival functions (KLS), measuring the distance between an empirical and prescribed survival functions, has been used to estimate the parameter of Lindley distribution. The simulation studies have been carried out to compare the...

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Bibliographic Details
Main Authors: Sultan Parveen, Sanjay Kumar Singh, Umesh Singh, Dinesh Kumar
Format: Article
Language:English
Published: Austrian Statistical Society 2019-07-01
Series:Austrian Journal of Statistics
Online Access:http://www.ajs.or.at/index.php/ajs/article/view/772
Description
Summary:A new point estimation method based on Kullback-Leibler divergence of survival functions (KLS), measuring the distance between an empirical and prescribed survival functions, has been used to estimate the parameter of Lindley distribution. The simulation studies have been carried out to compare the performance of the proposed estimator with the corresponding Least square (LS), Maximum likelihood (ML) and Maximum product spacing (MPS) methods of estimation.
ISSN:1026-597X