Tail-sensitive Gaussian asymptotics for marginals of concentrated measures in high dimension
| dc.creator | Sodin, Sasha | |
| dc.date | 2005-01-22 | |
| dc.date | 2005-08-12 | |
| dc.date.accessioned | 2026-07-07T08:25:57Z | |
| dc.date.available | 2026-07-07T08:25:57Z | |
| dc.description | If the Euclidean norm is strongly concentrated with respect to a measure, the average distribution of an average marginal of this measure has Gaussian asymptotics that captures tail behaviour. If the marginals of the measure have exponential moments, Gaussian asymptotics for the distribution of the average marginal implies Gaussian asymptotics for the distribution of most individual marginals. We show applications to measures of geometric origin. | |
| dc.description | 30 pages; typos and minor errors corrected | |
| dc.identifier | https://arxiv.org/abs/math/0501382 | |
| dc.identifier | http://arxiv.org/abs/math/0501382 | |
| dc.identifier | Geometric aspects of functional analysis (Israel Seminar 2004 -- 2005), pp. 271--295, Lecture Notes in Math., 1910, Springer, Berlin, 2007 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/136790 | |
| dc.subject | Metric Geometry | |
| dc.subject | Probability | |
| dc.title | Tail-sensitive Gaussian asymptotics for marginals of concentrated measures in high dimension | |
| dc.type | text |