Optimal information usage in binary sequential hypothesis testing

Meik Doerpinghaus*, Izaak Neri, Edgar Roldan, Frank Juelicher

*Corresponding author for this work

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Abstract

An interesting question is whether an information theoretic interpretation can be given of optimal algorithms in sequential hypothesis testing. We prove that for the binary sequential probability ratio test of a continuous observation process, the mutual information between the observation process up to the decision time and the actual hypothesis conditioned on the decision variable is equal to zero. This result can be interpreted as an optimal usage of the information on the hypothesis available in the observations by the sequential probability ratio test. As a consequence, the mutual information between the random decision time of the sequential probability ratio test and the actual hypothesis conditioned on the decision variable is also equal to zero.

Original languageEnglish
Pages (from-to)77-87
Number of pages11
JournalTheory of Probability and Its Applications
Volume68
Issue number1
DOIs
Publication statusPublished - 4 May 2023

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