DocumentCode
891883
Title
On the converse theorem in statistical hypothesis testing for Markov chains
Author
Nakagawa, Kenji ; Kanaya, Fumio
Author_Institution
Dept. of Planning & Manage. of Sci., Nagaoka Univ. of Technol., Niigata, Japan
Volume
39
Issue
2
fYear
1993
fDate
3/1/1993 12:00:00 AM
Firstpage
629
Lastpage
633
Abstract
Hypothesis testing for two Markov chains is considered. Under the constraint that the error probability of the first kind is less than or equal to exp(-rn ), the error probability of the second kind is minimized. The geodesic that connects the two Markov chains is defined. By analyzing the geodesic, the power exponents are calculated and then represented in terms of Kullback-Leibler divergence
Keywords
Markov processes; differential geometry; error statistics; information theory; statistical analysis; Kullback-Leibler divergence; Markov chains; converse theorem; error probability; geodesic; information geometry; power exponents; statistical hypothesis testing; Error probability; Frequency; Information geometry; Information theory; Laboratories; Space stations; State-space methods; Technology management; Technology planning; Testing;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.212294
Filename
212294
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