Entropy bounds for discrete random variables via coupling

This work provides new bounds on the difference between the entropies of two discrete random variables in terms of the local and total variation distances between their probability mass functions. The derivation of the bounds relies on maximal couplings, and the bounds apply to discrete random variables which are defined over finite or countably infinite alphabets. Loosened versions of these bounds are demonstrated to reproduce some previously reported results. The use of the new entropy bounds is exemplified for the Poisson approximation, where bounds on the local and total variation distances follow from Stein's method. The full paper version for this work is available at http://arxiv.org/abs/1209.5259.