Kullback's inequality
In information theory and statistics, Kullback's inequality is a lower bound on the Kullback–Leibler divergence expressed in terms of the large deviations rate function. If P and Q are probability distributions on the real line, such that P is absolutely continuous with respect to Q, i.e. P<<Q, and whose first moments exist, then where is the rate function, i.e. the convex conjugate of the cumulant-generating function, of , and is the first moment of The Cramér–Rao bound is a corollary of this result.
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Kullback's inequality
In information theory and statistics, Kullback's inequality is a lower bound on the Kullback–Leibler divergence expressed in terms of the large deviations rate function. If P and Q are probability distributions on the real line, such that P is absolutely continuous with respect to Q, i.e. P<<Q, and whose first moments exist, then where is the rate function, i.e. the convex conjugate of the cumulant-generating function, of , and is the first moment of The Cramér–Rao bound is a corollary of this result.
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In information theory and stat ...... is a corollary of this result.
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Kullbackova nerovnost je v teo ...... em Kullbackovy nerovnosti je .
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In information theory and stat ...... is a corollary of this result.
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Kullbackova nerovnost je v teo ...... em Kullbackovy nerovnosti je .
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Kullback's inequality
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Kullbackova nerovnost
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