TESTING FOR INDEPEDENCE IN MULTIVARIATE EXPONENTIAL DISTRIBUTIONS2

In this paper the work of Weier & Basu (1980) is extended to a special case of the trivariate exponential distributions and to the general k-variate case. In the trivariate case several statistics are derived including one based on the likelihood ratio approach and the locally most powerful rank statistic, and power studies are carried out. The general k-variate model is derived, and testing for independence is shown to reduce to a solved problem.     

GOODNESS-OF-FIT AND DISCORDANCY TESTS FOR SAMPLES FROM THE WATSON DISTRIBUTION ON THE SPHERE

The only parametric model in current use for axial data from a rotationally symmetric bipolar or girdle distribution on the sphere is the Watson distribution. This paper develops methods for evaluating the model as a fit to data using graphical and formal goodness-of-fit tests, and tests of discordancy.