Testing the Validity of Lindley Model Based on Nonparametric Probability Density Functions of Entropy Estimators: Accepted - March 2024

Hadi Alizadeh Noughabi; Mohammad Shafaei Noughabi

Forthcoming

Testing the Validity of Lindley Model Based on Nonparametric Probability Density Functions of Entropy Estimators

Accepted - March 2024

Authors

Hadi Alizadeh Noughabi University of Birjand https://orcid.org/0000-0002-7515-1896
Mohammad Shafaei Noughabi University of Gonabad https://orcid.org/0000-0001-5412-5560

Keywords:

Lindley distribution, Entropy, Kullback-Leibler information, Critical points, Test power, Monte Carlo simulation

Abstract

The Lindley distribution is one of the fundamental models applied for reliability models and in the present article, we propose some test statistics for testing the validity of Lindley model based on correcting moments of nonparametric probability density functions of entropy estimators. Critical points and type I error of the tests are obtained and power values of the tests are computed by Monte Carlo simulation. We show that the proposed tests are more powerful than competitor tests. Finally, the proposed tests are illustrated by a real data example.

Downloads

FP_REVSTAT2024_mar1

Published

2024-03-07

How to Cite

Alizadeh Noughabi, H., & Shafaei Noughabi, M. (2024). Testing the Validity of Lindley Model Based on Nonparametric Probability Density Functions of Entropy Estimators: Accepted - March 2024. REVSTAT-Statistical Journal. Retrieved from https://revstat.ine.pt/index.php/REVSTAT/article/view/671