Indexing metadata

Laha-Lukacs properties of some free processes


 
Dublin Core PKP Metadata Items Metadata for this Document
 
1. Title Title of document Laha-Lukacs properties of some free processes
 
2. Creator Author's name, affiliation, country Wiktor Ejsmont; University of Wroclaw; Poland
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) Free Meixner law; conditional expectation; free cumulants; Laha-Lukacs theorem; noncommutative quadratic regression; von Neumann algebras.
 
3. Subject Subject classification 46L54 ; 46L53
 
4. Description Abstract

We study the Laha-Lukacs property of the free Meixner laws (processes). We prove that some families of free Meixner distribution have the linear regression function. We also show that this families have the property of quadratic conditional variances.
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s) Research partially supported by Polish MNiSW grant NN201 364436
 
7. Date (YYYY-MM-DD) 2012-03-09
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier http://ecp.ejpecp.org/article/view/1865
 
10. Identifier Digital Object Identifier 10.1214/ECP.v17-1865
 
11. Source Journal/conference title; vol., no. (year) Electronic Communications in 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.