By Topic

On universal hypotheses testing via large deviations

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
O. Zeitouni ; Israel Inst. of Technol., Haifa, Israel ; M. Gutman

A prototype problem in hypotheses testing is discussed. The problem of deciding whether an i.i.d. sequence of random variables has originated from a known source P1 or an unknown source P2 is considered. The exponential rate of decrease in type II probability of error under a constraint on the minimal rate of decrease in type I probability of error is chosen for a criterion of optimality. Using large deviations estimates, a decision rule that is based on the relative entropy of the empirical measure with respect to P1 is proposed. In the case of discrete random variables, this approach yields weaker results than the combinatorial approach used by Hoeffding (1965). However, it enables the analysis to be extended to the general case of Rn-valued random variables. Finally, the results are extended to the case where P1 is an unknown parameter-dependent distribution that is known to belong to a set of distributions (P01, θ∈Θ)

Published in:

IEEE Transactions on Information Theory  (Volume:37 ,  Issue: 2 )