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arxiv: 1207.6618 · v1 · pith:O3RV6GYZnew · submitted 2012-07-27 · 🧮 math.PR · math.MG

Moment estimates for convex measures

classification 🧮 math.PR math.MG
keywords sigmaadditioncenteredconcaveconstantconvexdependsestimates
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Let $p\geq 1$, $\eps >0$, $r\geq (1+\eps) p$, and $X$ be a $(-1/r)$-concave random vector in $\R^n$ with Euclidean norm $|X|$. We prove that $(\E |X|^{p})^{1/{p}}\leq c (C(\eps) \E|X|+\sigma_{p}(X))$, where $\sigma_{p}(X)=\sup_{|z|\leq 1}(\E|<z,X>|^{p})^{1/p}$, $C(\eps)$ depends only on $\eps$ and $c$ is a universal constant. Moreover, if in addition $X$ is centered then $(\E |X|^{-p})^{-1/{p}}\geq c(\eps) (\E|X| - C \sigma_{p}(X))$.

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