The Prékopa–Leindler inequality is a fundamental result in the field of convex analysis and probability theory. It provides a way to compare the integrals of certain convex functions over different sets.
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In the finite, nonzero normalization, let , let be nonnegative integrable functions on with , and let be a nonnegative measurable function. If they satisfy for all , then their Lebesgue integrals obeyThe quantile derivative identity and monotone substitution inequality prove the one-dimensional case; Tonelli theorem extends it by induction. It implies the Brunn–Minkowski inequality.