Tests for circular symmetry of complex-valued random vectors

Norbert Henze (), Pierre Lafaye De Micheaux () and Simos G. Meintanis ()
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Norbert Henze: Karlsruhe Institute of Technology (KIT)
Pierre Lafaye De Micheaux: UNSW Sydney
Simos G. Meintanis: National and Kapodistrian University of Athens

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2022, vol. 31, issue 2, No 14, 488-518

Abstract: Abstract We propose tests for the null hypothesis that the law of a complex-valued random vector is circularly symmetric. The test criteria are formulated as $$L^2$$ L 2 -type criteria based on empirical characteristic functions, and they are convenient from the computational point of view. Asymptotic as well as Monte Carlo results are presented. Applications on real data are also reported. An R package called CircSymTest is available from the authors.

Keywords: Complex-valued random variable; Characteristic function; Goodness-of-fit test; 62H15; 62G09; 62P12; 62P30 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11749-021-00788-6

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