4 research outputs found
On the Equivalence of f-Divergence Balls and Density Bands in Robust Detection
The paper deals with minimax optimal statistical tests for two composite
hypotheses, where each hypothesis is defined by a non-parametric uncertainty
set of feasible distributions. It is shown that for every pair of uncertainty
sets of the f-divergence ball type, a pair of uncertainty sets of the density
band type can be constructed, which is equivalent in the sense that it admits
the same pair of least favorable distributions. This result implies that robust
tests under -divergence ball uncertainty, which are typically only minimax
optimal for the single sample case, are also fixed sample size minimax optimal
with respect to the equivalent density band uncertainty sets.Comment: 5 pages, 1 figure, accepted for publication in the Proceedings of the
IEEE International Conference on Acoustics, Speech, and Signal Processing
(ICASSP) 201
Robust Hypothesis Testing With Squared Hellinger Distance
Publication in the conference proceedings of EUSIPCO, Lisbon, Portugal, 201