In this paper we tackle the ANOVA problem for directional data (with particular emphasison geological data) by having recourse to the Le Cam methodology usually reserved for linearmultivariate analysis. We construct locally and asymptotically most stringent parametric testsfor ANOVA for...

We tackle the classical two-sample spherical location problem for directional data by having recourse to the Le Cam methodology, habitually used in classical linear multivariate analysis. More precisely we construct locally and asymptotically optimal (in the maximin sense) parametric tests,...

One-sample and multi-sample tests on the concentration parameter of Fisher-vonMises-Langevin (FvML) distributions have been well studied in the literature. However,only very little is known about their behavior under local alternatives, whichis due to complications inherent to the curved nature...

type="main" xml:id="insr12047-abs-0001" <title type="main">Summary</title>One-sample and multi-sample tests on the concentration parameter of Fisher-von Mises-Langevin distributions on (hyper-)spheres have been well studied in the literature. However, only little is known about their behaviour under local alternatives,...

We consider asymptotic inference for the concentration of directional data. More precisely, wepropose tests for concentration (i) in the low-dimensional case where the sample size n goes to infinity andthe dimension p remains fixed, and (ii) in the high-dimensional case where both n and p become...