The standard normal distribution $\Phi$ on $\mathbb{R}^d$ satisfies
$\Phi((\partial C)^\varepsilon)\leq c_d \varepsilon$, for all $\varepsilon >
0$ and for all convex subsets $C \subset \mathbb{R}^d$, with a constant $c_d$
which depends on the dimension $d$ only. Here $\partial C$ denotes the boundary
of $C$, and $(\partial C)^\epsilon$ stands for the $\epsilon$-neighborhood of
$\partial C$. Such bounds for the normal measure of convex shells are
extensively used to estimate the accuracy of normal approximations.
¶ We extend the inequality to all (nondegenerate) stable distributions
on $\mathbb{R}^d$, with a constant which depends on the dimension, the
characteristic exponent and the spectral measure of the distribution only. As a
corollary we provide an explicit bound for the accuracy of stable
approximations on the class of all convex subsets of $\mathbb{R}^d$ .
@article{1019160335,
author = {Bentkus, V. and Juozulynas, A. and Paulauskas, V.},
title = {Bounds for stable measures of convex shells and stable
approximations},
journal = {Ann. Probab.},
volume = {28},
number = {1},
year = {2000},
pages = { 1280-1300},
language = {en},
url = {http://dml.mathdoc.fr/item/1019160335}
}
Bentkus, V.; Juozulynas, A.; Paulauskas, V. Bounds for stable measures of convex shells and stable
approximations. Ann. Probab., Tome 28 (2000) no. 1, pp. 1280-1300. http://gdmltest.u-ga.fr/item/1019160335/