EJP Reading Tools

A Williams decomposition for spatially dependent superprocesses

Dublin Core		PKP Metadata Items	Metadata for this Document
1.	Title	Title of document	A Williams decomposition for spatially dependent superprocesses
2.	Creator	Author's name, affiliation, country	Jean-François Delmas; Université Paris-Est, Cermics; France
2.	Creator	Author's name, affiliation, country	Olivier Hénard; Université Paris-Est, Cermics; France
3.	Subject	Discipline(s)
3.	Subject	Keyword(s)	Spatially dependent superprocess, Williams' decomposition, genealogy, h-transform, Q-process.
3.	Subject	Subject classification	60J25; 60J55; 60J80
4.	Description	Abstract	We present a genealogy for superprocesses with a non-homogeneous quadratic branching mechanism, relying on a weighted version of the superprocess introduced by Engländer and Pinsky and a Girsanov theorem. We then decompose this genealogy with respect to the last individual alive (Williams' decomposition). Letting the extinction time tend to infinity, we get the Q-process by looking at the superprocess from the root, and define another process by looking from the top. Examples including the multitype Feller diffusion (investigated by Champagnat and Roelly) and the superdiffusion are provided.
5.	Publisher	Organizing agency, location
6.	Contributor	Sponsor(s)	Agence Nationale de la Recherche, ANR-08-BLAN-0190.
7.	Date	(YYYY-MM-DD)	2013-03-12
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/1801
10.	Identifier	Digital Object Identifier	10.1214/EJP.v18-1801
11.	Source	Journal/conference title; vol., no. (year)	Electronic Journal of Probability; Vol 18
12.	Language	English=en	en
14.	Coverage	Geo-spatial location, chronological period, research sample (gender, age, etc.)
15.	Rights	Copyright and permissions	The Electronic Journal of Probability applies the Creative Commons Attribution License (CCAL) to all articles we publish in this journal. Under the CCAL, authors retain ownership of the copyright for their article, but authors allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles published in EJP, so long as the original authors and source are credited. This broad license was developed to facilitate open access to, and free use of, original works of all types. Applying this standard license to your work will ensure your right to make your work freely and openly available. Summary of the Creative Commons Attribution License You are free to copy, distribute, display, and perform the work to make derivative works to make commercial use of the work under the following condition of Attribution: others must attribute the work if displayed on the web or stored in any electronic archive by making a link back to the website of EJP via its Digital Object Identifier (DOI), or if published in other media by acknowledging prior publication in this Journal with a precise citation including the DOI. For any further reuse or distribution, the same terms apply. Any of these conditions can be waived by permission of the Corresponding Author.