Poisson limits for a hard-core clustering model

Roy Saunders, Richard J. Kryscio and Gerald M. Funk

Stochastic Processes and their Applications, 1981, vol. 12, issue 1, 97-106

Abstract: Let X1n,...,X>nn denote the locations of n points in a bounded, [gamma]-dimensional, Euclidean region Dn which has positive [gamma]-dimensional Lebesgue measure [mu](Dn). Let {Yn(r): r> 0} be the interpoint distance process for these points where Yn(r) is the number of pairs of points(Xin, Xin) which with i in|| [infinity] and [mu](Dn) --> [infinity], and the joint density of X1n,...,Xnnis of the form where r0 is a positive constant and Cn is a normalizing constant. These joint densities modify the Strauss [11] clustering model densities by introducing a hard-core component (no two points can have ||Xin - Xin|| 0. Statistical applications are discussed.

Keywords: Clustering; model; hard-core; Poisson; process; raduis; of; influence; sparseness; weak; convergence (search for similar items in EconPapers)
Date: 1981
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0304-4149(81)90014-4
Full text for ScienceDirect subscribers only

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:eee:spapps:v:12:y:1981:i:1:p:97-106

Ordering information: This journal article can be ordered from
http://http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Stochastic Processes and their Applications is currently edited by T. Mikosch

More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().