Title :
When is the generalized likelihood ratio test optimal?
Author :
Zeitouni, Ofer ; Ziv, Jacob ; Merhav, Neri
Author_Institution :
Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel
fDate :
9/1/1992 12:00:00 AM
Abstract :
The generalized likelihood ratio test (GLRT), which is commonly used in composite hypothesis testing problems, is investigated. Conditions for asymptotic optimality of the GLRT in the Neyman-Pearson sense are studied and discussed. First, a general necessary and sufficient condition is established, and then based on this, a sufficient condition, which is easier to verify, is derived. A counterexample where the GLRT is not optimal, is provided as well. A conjecture is stated concerning the optimality of the GLRT for the class of finite-state sources
Keywords :
information theory; Neyman-Pearson sense; asymptotic optimality; finite-state sources; generalized likelihood ratio test; hypothesis testing; Concrete; Coordinate measuring machines; Information theory; Jacobian matrices; Light rail systems; Prototypes; Sufficient conditions; Testing;
Journal_Title :
Information Theory, IEEE Transactions on
