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A Compensator Characterization of Point Processes on TopologicalLattices

Dublin Core		PKP Metadata Items	Metadata for this Document
1.	Title	Title of document	A Compensator Characterization of Point Processes on TopologicalLattices
2.	Creator	Author's name, affiliation, country	B.Gail Ivanoff; University of Ottawa
2.	Creator	Author's name, affiliation, country	Ely Merzbach; Bar-Ilan University
2.	Creator	Author's name, affiliation, country	Mathieu Plante; No affiliation
3.	Subject	Discipline(s)
3.	Subject	Keyword(s)	point process, compensator, partial order, single jump process, partial sum process,adapted random set, renewal process,Poisson process, multiparameter martingale
3.	Subject	Subject classification	60K05;60G55;60G48
4.	Description	Abstract	We resolve the longstanding question of how to define the compensator of a point process on a general partially ordered set in such a way that the compensator exists, is unique, and characterizes the law of the process. We define a family of one-parameter compensators and prove that this family is unique in some sense and characterizes the finite dimensional distributions of a totally ordered point process. This result can then be applied to a general point process since we prove that such a process can be embedded into a totally ordered point process on a larger space. We present some examples, including the partial sum multiparameter process, single line point processes, multiparameter renewal processes, and obtain a new characterization of the two-parameter Poisson process
5.	Publisher	Organizing agency, location
6.	Contributor	Sponsor(s)
7.	Date	(YYYY-MM-DD)	2007-01-14
8.	Type	Status & genre	Peer-reviewed Article
8.	Type	Type
9.	Format	File format	PDF
10.	Identifier	Uniform Resource Identifier	http://ejp.ejpecp.org/article/view/390
10.	Identifier	Digital Object Identifier	10.1214/EJP.v12-390
11.	Source	Journal/conference title; vol., no. (year)	Electronic Journal of Probability; Vol 12
12.	Language	English=en
14.	Coverage	Geo-spatial location, chronological period, research sample (gender, age, etc.)
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