Testing the Gaussianity of a random process has been identified as an important problem in many engineering applications. Tests based on the bispectrum such as Subba Rao and Gabr's (1980) test or Hinich's (1982) test for Gaussianity have been proposed more than a decade ago. They have received considerable interest and application among the signal processing community. However, their application is limited to cases where a large amount of data is available. To overcome this problem, we incorporate the bootstrap into the bispectrum based Gaussianity test, and demonstrate how we can achieve high power. The proposed bootstrap procedure can also be used for setting confidence bands for bispectra.
['Abdelhak M. Zoubir', 'D.R. Iskander']
A bispectrum based Gaussianity test using the bootstrap