DocumentCode
1030790
Title
On tests for normality
Author
Steinberg, Y. ; Zeitouni, O.
Author_Institution
Dept. of Electr. Eng., Princeton Univ., NJ, USA
Volume
38
Issue
6
fYear
1992
fDate
11/1/1992 12:00:00 AM
Firstpage
1779
Lastpage
1787
Abstract
The problem of deciding whether a sample of a random field was generated by a Gaussian distribution is considered. Based on extensions of large deviation estimates due to M.D. Donsker and S.R.S. Varadhan (1985), a test that is optimal in a generalized Neyman-Pearson sense is proposed. This test turns out to depend on properties of the entropy of Gaussian processes and does not depend on cumulant computations
Keywords
entropy; information theory; random processes; Gaussian distribution; Gaussian processes; entropy; generalized Neyman-Pearson sense; information theory; normality tests; optimal test; random field; Economic indicators; Entropy; Gaussian distribution; Gaussian processes; Hydrogen; Particle measurements; Spectral analysis; Testing;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.165450
Filename
165450
Link To Document