Probabilistic Extensions of the Erdős–Ko–Rado Property
Anna Celaya (),
Anant P. Godbole () and
Mandy Rae Schleifer ()
Additional contact information
Anna Celaya: University of Wisconsin
Anant P. Godbole: East Tennessee State University
Mandy Rae Schleifer: Duquesne University
Methodology and Computing in Applied Probability, 2006, vol. 8, issue 3, 357-371
Abstract:
Abstract The classical Erdős–Ko–Rado (EKR) Theorem states that if we choose a family of subsets, each of size k, from a fixed set of size $n\ (n > 2k)$ , then the largest possible pairwise intersecting family has size $t ={n-1\choose k-1}$ . We consider the probability that a randomly selected family of size t=t n has the EKR property (pairwise nonempty intersection) as n and k=k n tend to infinity, the latter at a specific rate. As t gets large, the EKR property is less likely to occur, while as t gets smaller, the EKR property is satisfied with high probability. We derive the threshold value for t using Janson’s inequality. Using the Stein–Chen method we show that the distribution of X 0, defined as the number of disjoint pairs of subsets in our family, can be approximated by a Poisson distribution. We extend our results to yield similar conclusions for X i , the number of pairs of subsets that overlap in exactly i elements. Finally, we show that the joint distribution (X 0, X 1, ..., X b ) can be approximated by a multidimensional Poisson vector with independent components.
Keywords: Erdős–Ko–Rado (EKR) theorem; Pairwise nonempty intersection; Poisson distribution; Primary 60F05; 60C05; Secondary 05D05; 05D40 (search for similar items in EconPapers)
Date: 2006
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s11009-006-9751-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:metcap:v:8:y:2006:i:3:d:10.1007_s11009-006-9751-2
Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009
DOI: 10.1007/s11009-006-9751-2
Access Statistics for this article
Methodology and Computing in Applied Probability is currently edited by Joseph Glaz
More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().