Journal article
Functional strong laws of large numbers for Euler characteristic processes of extreme sample clouds
Extremes (Boston), Vol.24(4), pp.699-724
12/01/2021
DOI: 10.1007/s10687-021-00419-1
Abstract
To recover the topology of a manifold in the presence of heavy tailed or exponentially decaying noise, one must understand the behavior of geometric complexes whose points lie in the tail of these noise distributions. This study advances this line of inquiry, and demonstrates functional strong laws of large numbers for the Euler characteristic process of random geometric complexes formed by random points outside of an expanding ball in R-d. When the points are drawn from a heavy tailed distribution with a regularly varying tail, the Euler characteristic process grows at a regularly varying rate, and the scaled process converges uniformly and almost surely to a smooth function. When the points are drawn from a distribution with an exponentially decaying tail, the Euler characteristic process grows logarithmically, and the scaled process converges to another smooth function in the same sense. All of the limit theorems take place when the points inside the expanding ball are densely distributed, so that the simplex counts outside of the ball of all dimensions contribute to the Euler characteristic process.
Details
- Title: Subtitle
- Functional strong laws of large numbers for Euler characteristic processes of extreme sample clouds
- Creators
- Andrew M. Thomas - Purdue University West LafayetteTakashi Owada - Purdue University West Lafayette
- Resource Type
- Journal article
- Publication Details
- Extremes (Boston), Vol.24(4), pp.699-724
- Publisher
- Springer Nature
- DOI
- 10.1007/s10687-021-00419-1
- ISSN
- 1386-1999
- eISSN
- 1572-915X
- Number of pages
- 26
- Grant note
- 1811428 / National Science Foundation (NSF) grant, Division of Mathematical Sciences (DMS); National Science Foundation (NSF)
- Language
- English
- Date published
- 12/01/2021
- Academic Unit
- Statistics and Actuarial Science
- Record Identifier
- 9984446419202771
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