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
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