A unified approach to goodness-of-fit testing for spherical and hyperspherical data

Bruno Ebner (), Norbert Henze () and Simos Meintanis ()
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Bruno Ebner: Karlsruhe Institute of Technology (KIT)
Norbert Henze: Karlsruhe Institute of Technology (KIT)
Simos Meintanis: National and Kapodistrian University of Athens

Statistical Papers, 2024, vol. 65, issue 6, No 5, 3447-3475

Abstract: Abstract We propose a general and relatively simple method to construct goodness-of-fit tests on the sphere and the hypersphere. The method is based on the characterization of probability distributions via their characteristic function, and it leads to test criteria that are convenient regarding applications and consistent against arbitrary deviations from the model under test. We emphasize goodness-of-fit tests for spherical distributions due to their importance in applications and the relative scarcity of available methods.

Keywords: Goodness-of-fit test; Characteristic function; Resampling methods; Spherical distribution; 62H15; 62H11; 62G20 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s00362-024-01529-1

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