The likelihood-ratio event depends only on the type and is
equivalently . This constraint defines a closed subset of the finite probability simplex, so Sanov's upper bound gives the exponent
It is strictly positive: the only distribution with zero divergence from is , but violates the constraint because . Compactness and continuity under full support keep the infimum away from zero. This exponent is the Chernoff information between and .

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