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For any random variable XXX and estimator X^\hat{X}X^, E[(XāX^)2]ā„12Ļee2h[X]E\left[ (X-\hat{X})^{2} \right]\ge \frac{1}{2\pi e}e^{2h[X]}E[(XāX^)2]ā„2Ļe1āe2h[X]with equality if and only if XXX is Gaussian and X^=E[X]\hat{X}=E_{}\left[ X \right]X^=Eā[X].
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