Bayesian tests for circular uniformity

Circular data are measured in angles or directions, which occur a wide variety of scientific fields. An often investigated hypothesis is that circular uniformity, isotropy. Frequentist methods for assessing the uniformity null exist, but do not allow user faced with an insignificant result to distinguish lack power from support hypothesis. Bayesian tests, solve this issue and several others, developed here. They easy compute perform well, shown simulation. Two alternative hypotheses considered. One based on von Mises distribution performs well against unimodal alternatives. Another kernel density, acts as omnibus test all other scenarios. Assessing performance tests using different priors, it they powerful more elaborate conclusions than classical uniformity.