Goodness-of-fit tests for the weighted exponential distribution

In the new class of weighted exponential distributions was presented by Gupta and Kundu [1], the skewness parameter has been added to the exponential distribution. Therefore the weighted exponential distribution has the skewness and scale parameters. In this paper, we first study Anderson and Kolmogorov-Smirnov goodness of fit tests for this class with unknown parameters. Then, we apply bootstrap method for estimation of Anderson’s quantile and another method for Kolmogorov-Smirnov. We use the maximum likelihood method for estimation of parameters. Finally, we compare Kolmogorov-Smirnov and Anderson tests in a Monte Carlo simulation study. The results show that the Kolmogorov–Smirnov test has greater power than Anderson test.