Goodness of Fit Test and Test of Independence by Entropy

To test whether a set of data has a specific distribution or not, we can use the goodness of fit test. This test can be done by one of Pearson X 2 -statistic or the likelihood ratio statistic G 2 , which are asymptotically equal, and also by using the Kolmogorov-Smirnov statistic in continuous distributions. In this paper, we introduce a new test statistic for goodness of fit test which is based on entropy distance, and which can be applied for large sample sizes. We compare this new statistic with the classical test statistics X 2 , G 2 , and Tn by some simulation studies. We conclude that the new statistic is more sensitive than the usual statistics to the rejection of distributions which are almost closed to the desired distribution. Also for testing independence, a new test statistic based on mutual information is introduced.