Probability inequalities for convex sets and multidimensional concentration functions

This paper derives a sharp bound for the probability that a sum of independent symmetric random vectors lies in a symmetric convex set. In one dimension this bound is an improvement of an inequality first proved by Kolmogorov. The subject of multidimensional concentration functions is also treated.

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Year of publication:	1976
Authors:	Kanter, Marek
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 6.1976, 2, p. 222-236
Publisher:	Elsevier
Keywords:	Sums of independent random vectors convex set multidimensional concentration function

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005152784