Testing exponentiality using different entropy estimates based on Type II censored data : A Monte Carlo power comparison

Authors

  • Jalil Jarrahi 1Department of Mathematics, Birjand Branch, Islamic Azad University, Birjand, Iran
  • Hadi Alizadeh Noughabi Department of Statistics, University of Birjand, Birjand, Iran.

DOI:

https://doi.org/10.23055/ijietap.2017.24.5.3225

Keywords:

Testing exponentiality, Entropy estimator, Kullback-Leibler information, Type-II censoring, Monte Carlo simulation, Power study.

Abstract

The exponential distribution is commonly used to model and
examine lifetime data. When applying the exponential model, it is critical to
develop efficient goodness of fit tests. In this article, we first propose some
new entropy estimators for Type-II censored data and then introduce some
goodness of fit test statistics for the exponential distribution based on Type-II
censored data using different entropy estimators. The critical values of the tests
do not depend on the scale parameter of the exponential distribution and
therefore the proposed tests are exact. The critical values and powers of the
tests are obtained. The Monte Carlo simulation study indicates that the
proposed tests have higher powers than competing tests against the alternatives
with monotone increasing hazard functions. Real-life data examples
demonstrate the applicability of the proposed tests in practice.

Published

2018-01-11

How to Cite

Jarrahi, J., & Alizadeh Noughabi, H. (2018). Testing exponentiality using different entropy estimates based on Type II censored data : A Monte Carlo power comparison. International Journal of Industrial Engineering: Theory, Applications and Practice, 24(5). https://doi.org/10.23055/ijietap.2017.24.5.3225

Issue

Section

Modelling and Simulation