Testing Exponentiality Based on Renyi Entropy of Transformed Data

In this paper, we introduce new tests for exponentiality based on estimators of Renyi entropy of a continuous random variable. We first consider two transformations of the observations which turn the test of exponentiality into one of uniformity and use a corresponding test based on Renyi entropy. Critical values of the test statistics are computed by Monte Carlo simulations. Then, we compare powers of the tests for various alternatives and sample sizes with exponentiality tests based on Kullback-Leibler information proposed by Ebrahimi {et al.} (1992) and Choi {et al.} (2004). Our simulation results show that the proposed tests have higher powers than the competitor tests.