  The R\'enyi information measures are characterized in terms of their Shannon
counterparts, and properties of the former are recovered from first principle
via the associated properties of the latter. Motivated by this
characterization, a two-sensor composite hypothesis testing problem is
presented, and the optimal worst case miss-detection exponent is obtained in
terms of a R\'enyi divergence.
