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
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;
Conference_Titel :
Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on
Print_ISBN :
0-7803-3676-3
DOI :
10.1109/ICICS.1997.652173