Threshold for the expected measure of random polytopes

نویسندگان

چکیده

Abstract Let $$\mu $$ μ be a log-concave probability measure on $${\mathbb R}^n$$ R n and for any $$N>n$$ N > consider the random polytope $$K_N=\textrm{conv}\{X_1,\ldots ,X_N\}$$ K = conv { X 1 , … } , where $$X_1,X_2,\ldots 2 are independent points in distributed according to . We study question if there exists threshold expected of $$K_N$$ Our approach is based Cramer transform $$\Lambda _{\mu }^{*}$$ Λ ∗ examine existence moments all orders establish, under some conditions, sharp expectation {E}}_{\mu ^N}[\mu (K_N)]$$ E [ ( ) ] : it close 0 $$\ln N\ll {\mathbb }(\Lambda }^{*})$$ ln ≪ 1 N\gg ≫ The main condition that parameter $$\beta (\mu )=\textrm{Var}_{\mu }^{*})/({\mathbb }^{*}))^2$$ β Var / should small.

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We prove the central limit theorem for the volume and the f -vector of the random polytope Pn and the Poisson random polytope Πn in a fixed convex polytope P ⊂ IR. Here Pn is the convex hull of n random points in P , and Πn is the convex hull of the intersection of a Poisson process X(n), of intensity n, with P . A general lower bound on the variance is also proved. ∗Supported by Hungarian Nati...

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ژورنال

عنوان ژورنال: Mathematische Annalen

سال: 2023

ISSN: ['1432-1807', '0025-5831']

DOI: https://doi.org/10.1007/s00208-023-02600-2