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    Öğe
    Bayesian Binary Hypothesis Testing under Model Uncertainty
    (Institute of Electrical and Electronics Engineers Inc., 2020) Afser, Huseyin; Yildirim, Ugur
    We consider Bayesian binary hypothesis testing problem when there is only partial knowledge about one of the distributions, while the other distribution is fully known. Specifically, let P1 and P2 be the distributions under two hypothesis, where P2 is known and P1 is unknown. We propose a test and show that if the Chernoff distance between P1 and P2 is known to be larger than ?, an error exponent ?-?, ?>0, can be achieved in the Bayesian setting. If the Chernoff distance between P1 and P2 is not known, but another distribution Q1 known such that l1 distance between P1 and Q1 is known the smaller than ?, then the same test can be applied, and it coincides with the robust hypothesis testing methods existing in the literature. © 2020 IEEE.
  • [ X ]
    Öğe
    Bayesian Binary Hypothesis Testing Under Model Uncertainty
    (IEEE, 2020) Afser, Huseyin; Yildirim, Ugur
    We consider Bayesian binary hypothesis testing problem when there is only partial knowledge about one of the distributions, while the other distribution is fully known. Specifically, let P-1 and P-2 be the distributions under two hypothesis, where P-2 is known and P-1 is unknown. We propose a test and show that if the Chernoff distance between P-1 and P-2 is known to be larger than Phi, an error exponent Phi,- epsilon, epsilon > 0, can be achieved in the Bayesian setting. If the Chernoff distance between P-1 and P-2 is not known, but another distribution Q(1) known such that l(1) distance between P-1 and Q(1) is known the smaller than a, then the same test can be applied, and it coincides with the robust hypothesis testing methods existing in the literature.