Testing equivalence to power law distributions

Abstract

We introduce a new test for equivalence to power law distributions. The test is based on the minimum distance method. The critical value can be calculated using the asymptotic approximation or can be estimated by bootstrapping. We apply the proposed test to two real data sets: the city sizes in Germany and the Open American National Corpus. The finite sample performance is studied by simulations, which are based on these real data sets.