• DocumentCode
    2239590
  • Title

    A new approach to testing Gaussianity with the characteristic function

  • Author

    Brown, Christopher L. ; Zoubir, Abdelhak M.

  • Author_Institution
    Signal Process. Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
  • fYear
    1997
  • fDate
    9-12 Sep 1997
  • Firstpage
    1198
  • Abstract
    The use of an alternative to the kernel characteristic function estimator and empirical characteristic function based Gaussianity tests, has been proposed. It uses a smoothed difference function found by applying a smoothing kernel to the difference between the empirical characteristic function and the characteristic function under H0 . After an investigation into the choice of test statistics, an omnibus test is proposed that is powerful against a wide range of alternatives. Different test statistics are proposed to increase power against symmetric and/or asymmetric alternatives. Simulations are performed, confirming the increased power due to the smoothed difference function, as well as the rationale behind the choice of test statistics
  • Keywords
    Gaussian processes; functional analysis; smoothing methods; statistical analysis; Gaussianity testing; Monte Carlo simulations; empirical characteristic function; kernel characteristic function estimator; smoothed difference function; smoothing kernel; stationary process; test statistics; Australia; Gaussian processes; Kernel; Performance evaluation; Random variables; Signal processing; Smoothing methods; Statistical analysis; Statistical distributions; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on
  • Print_ISBN
    0-7803-3676-3
  • Type

    conf

  • DOI
    10.1109/ICICS.1997.652173
  • Filename
    652173