In our project we recreated the distribution-free density-based likelihood technique, applied to test for goodness-of-fit, described in the paper. Authors focus on tests for normality and uniformity. The well-known goodness-of-fit tests based on sample entropy are shown to be a product of the proposed empirical likelihood (EL) methodology. Estimation of the sample entropy has been not invariantly defined in literature, and hence this estimation produces tests that are difficult to be applied to real data studies. The proposed EL approach defines clear forms of the entropy-based tests. Monte Carlo simulation results confirm the preference of the proposed method from a power perspective.
All calculations are presented in our notebook