Abstract
We prove the Shepp–Olkin conjecture, which states that the entropy of the sum of independent Bernoulli random variables is concave in the parameters of the individual random variables. Our proof refines an argument previously presented by the same authors, which resolved the conjecture in the monotonic case (where all the parameters are simultaneously increasing). In fact, we show that the monotonic case is the worst case, using a careful analysis of concavity properties of the derivatives of the probability mass function. We propose a generalization of Shepp and Olkin’s original conjecture, to consider Rényi and Tsallis entropies.
Citation
Erwan Hillion. Oliver Johnson. "A proof of the Shepp–Olkin entropy concavity conjecture." Bernoulli 23 (4B) 3638 - 3649, November 2017. https://doi.org/10.3150/16-BEJ860
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