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Almost sure limit sets of random samples in ℝd

Published online by Cambridge University Press:  01 July 2016

Richard A. Davis ,
Edward Mulrow  and
Sidney I. Resnick
Richard A. Davis*
Affiliation:
Colorado State University
Edward Mulrow*
Affiliation:
Southern Illinois University
Sidney I. Resnick*
Affiliation:
Cornell University
*
∗ Postal address: Department of Statistics, Colorado State University, Fort Collins, CO 80523, USA.
∗∗ Postal address: Department of Mathematics, Southern Illinois University, Carbondale, IL 62910, USA.
∗∗∗ Postal address: OR/IE, Upson Hall, Cornell University, Ithaca, NY 14853, USA.
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Abstract

If {Xj , } is a sequence of i.i.d. random vectors in , when do there exist scaling constants bn > 0 such that the sequence of random sets converges almost surely in the space of compact subsets of to a limit set? A multivariate regular variation condition on a properly defined distribution tail guarantees the almost sure convergence but without certain regularity conditions surprises can occur. When a density exists, an exponential form of regular variation plus some regularity guarantees the convergence.

Keywords

RANDOM SETSMULTIVARIATE REGULAR VARIATIONALMOST SURE CONVERGENCEHAUSDORFF METRICCONVEX HULL

Information

Type
Research Article
Information
Advances in Applied Probability , Volume 20 , Issue 3 , September 1988 , pp. 573 - 599
Copyright
Copyright © Applied Probability Trust 1988 

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Footnotes

Support gratefully acknowledged from NSF Grant DMS 85–01763 at Colorado State University.

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