Indexing metadata

Multidimensional q-Normal and Related Distributions - Markov Case


 
Dublin Core PKP Metadata Items Metadata for this Document
 
1. Title Title of document Multidimensional q-Normal and Related Distributions - Markov Case
 
2. Creator Author's name, affiliation, country Pawel Jerzy Szablowski; Warsaw University of Technology; Poland
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) Normal distribution, Poisson-Mehler expansion formula,q-Hermite, Al-Salam-Chihara Chebyshev, Askey-Wilson polynomials, Markovproperty
 
3. Subject Subject classification 62H10; 62E10; 60E05;60E99
 
4. Description Abstract We define and study distributions in $\mathbb{R}^d$ that we call $q$-Normal. For $q=1$ they are really multidimensional Normal, for $q$ in $(-1,1)$ they have densities, compact support and many properties that resemble properties of ordinary multidimensional Normal distribution. We also consider some generalizations of these distributions and indicate close relationship of these distributions to Askey-Wilson weight function i.e. weight with respect to which Askey-Wilson polynomials are orthogonal and prove some properties of this weight function. In particular we prove a generalization of Poisson-Mehler expansion formula
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s)
 
7. Date (YYYY-MM-DD) 2010-08-14
 
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/796
 
10. Identifier Digital Object Identifier 10.1214/EJP.v15-796
 
11. Source Journal/conference title; vol., no. (year) Electronic Journal of Probability; Vol 15
 
12. Language English=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.