A test for aliasing using bispectral analysis

Abstract

Aliasing is a signal-confounding problem that arises when a continuous-time signal is sampled at a rate slower than twice the highest frequency component of a Fourier series representation of the signal. Aliasing can be especially serious for social-science time series applications, since the sampling designs used to construct most social-science data bases are fixed by considerations other than the nature of the underlying continuous-time mechanisms. After collecting sampled data, it is of value to test the observations for the presence of aliasing. It is shown that the nature of the support set of a sampled band-limited stationary signal can be used to motivate an amended version of the Hinich bispectrum test for Gaussianity (Hinich 1982) as a test for aliasing. © 1976 Taylor & Francis Group, LLC.