Title :
A new lower bound for multiple hypothesis testing
Author_Institution :
Lab. de Probabilites et Modeles Aleatoires, Univ. Paris VI
fDate :
4/1/2005 12:00:00 AM
Abstract :
The purpose of this correspondence is to give a new, easily tractable, and sharp lower bound for the maximal error in multiple hypothesis testing with an application to nonasymptotic lower bounds for the minimax risk of estimators
Keywords :
information theory; minimax techniques; probability; maximal error; multiple hypothesis testing; nonasymptotic lower bound; Books; Decoding; Extraterrestrial measurements; Minimax techniques; Parameter estimation; Random variables; Statistical distributions; Statistics; Testing; Fano´s lemma; minimax risk; multiple hypothesis testing;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2005.844101
