Inference for spherical location under high concentration

DOI10.1214/19-AOS1918zbMath1460.62028arXiv1901.00359OpenAlexW3003721943MaRDI QIDQ2215768

Davy Paindaveine, Thomas Verdebout

Publication date: 14 December 2020

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1901.00359

zbMATH Keywords

local asymptotic normalitysuperefficiencydirectional statisticsLe Cam's asymptotic theory of statistical experimentsconcentrated distributions

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20) Applications of statistics to environmental and related topics (62P12) Parametric inference under constraints (62F30) Applications of statistics to physics (62P35) Asymptotic properties of parametric tests (62F05) Geo-electricity and geomagnetism (86A25)

Related Items (6)

Asymptotic efficiency of some nonparametric tests for location on hyperspheres ⋮ Detecting the direction of a signal on high-dimensional spheres: non-null and Le Cam optimality results ⋮ Recent advances in directional statistics ⋮ Geodesic projection of the von Mises-Fisher distribution for projection pursuit of directional data ⋮ The entropy based goodness of fit tests for generalized von Mises-Fisher distributions and beyond ⋮ Testing uniformity on high-dimensional spheres: the non-null behaviour of the Bingham test

Uses Software

• rotasym

Cites Work

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