Asymptotic Robust Hypothesis Testing Based on Moment Classes
نویسندگان
چکیده
A robust hypothesis testing framework is introduced in which candidate hypotheses are characterized by moment classes. It is shown that there exists a test sequence that is asymptotically optimal in the min-max sense, and that it is expressed as a comparison of a log-linear combination of the constraint functions to a pre-determined threshold. Algorithms are described to compute the optimal test and applications of the robust hypothesis testing framework are discussed.
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