Indexing metadata

Distribution of the supremum location of stationary processes


 
Dublin Core PKP Metadata Items Metadata for this Document
 
1. Title Title of document Distribution of the supremum location of stationary processes
 
2. Creator Author's name, affiliation, country Gennady Samorodnitsky; Cornell University; United States
 
2. Creator Author's name, affiliation, country Yi Shen; Cornell University; United States
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) stationary process ; global supremum location ; bounded variation ; strong mixing
 
3. Subject Subject classification 60G10 ; 60G17
 
4. Description Abstract

The location of the unique supremum of a stationary process on an interval does not need to be uniformly distributed over that interval. We describe all possible distributions of the supremum location for a broad class of such stationary processes. We show that, in the strongly mixing case, this distribution does tend to the uniform in a certain sense as the length of the interval increases to infinity.

 
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s) ARO ; NSA ; NSF
 
7. Date (YYYY-MM-DD) 2012-06-02
 
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/2069
 
10. Identifier Digital Object Identifier 10.1214/EJP.v17-2069
 
11. Source Journal/conference title; vol., no. (year) Electronic Journal of Probability; Vol 17
 
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.