Classical estimation techniques for linear models either are inconsistent, or perform somewhat poorly under stable error densities; most of them are not even rate-optimal. In this paper, we develop an original R-estimation method and investigate its asymptotic performances under stable...

Linear models with stable error densities are considered. The local asymptotic normality of the resulting model is established. We use this result, combined with Le~Cam's third lemma, to obtain local powers of various classical rank tests (Wilcoxon's and van der Waerden's test, the median test,...

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,...