• DocumentCode
    3103560
  • Title

    Testing multivariate Gaussianity with the characteristic function

  • Author

    Zoubir, A.M. ; Brown, C.L. ; Boashash, B.

  • Author_Institution
    Signal Process. Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
  • fYear
    1997
  • fDate
    21-23 Jul 1997
  • Firstpage
    438
  • Lastpage
    442
  • Abstract
    A modification to a previously developed characteristic function based Gaussianity test is proposed. The power of the test is consequently improved. This test is then extended to the multivariate case, allowing it to be applied to correlated data. Monte Carlo simulations are performed to compare power with two other tests for multivariate Gaussianity, with encouraging results
  • Keywords
    Gaussian processes; Monte Carlo methods; correlation theory; higher order statistics; signal processing; smoothing methods; testing; Monte Carlo simulations; characteristic function; correlated data; testing multivariate Gaussianity; Australia; Gaussian processes; H infinity control; Kernel; Performance evaluation; Reactive power; Signal processing; Smoothing methods; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on
  • Conference_Location
    Banff, Alta.
  • Print_ISBN
    0-8186-8005-9
  • Type

    conf

  • DOI
    10.1109/HOST.1997.613563
  • Filename
    613563
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3103560