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Point process convergence for symmetric functions of high-dimensional random vectors.
- Source :
- Extremes; Jun2024, Vol. 27 Issue 2, p185-217, 33p
- Publication Year :
- 2024
-
Abstract
- The convergence of a sequence of point processes with dependent points, defined by a symmetric function of iid high-dimensional random vectors, to a Poisson random measure is proved. This also implies the convergence of the joint distribution of a fixed number of upper order statistics. As applications of the result a generalization of maximum convergence to point process convergence is given for simple linear rank statistics, rank-type U-statistics and the entries of sample covariance matrices. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13861999
- Volume :
- 27
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Extremes
- Publication Type :
- Academic Journal
- Accession number :
- 177148219
- Full Text :
- https://doi.org/10.1007/s10687-023-00482-w