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Symmetry, Integrability and Geometry: Methods and Applications, 2008, Volume 4, 089, 18 pp.
DOI: https://doi.org/10.3842/SIGMA.2008.089
(Mi sigma342)
 

This article is cited in 29 scientific papers (total in 29 papers)

A Probablistic Origin for a New Class of Bivariate Polynomials

Michael R. Hoare, Mizan Rahmana

a School of Mathematics and Statistics, Carleton University, Ottawa, ON K1S 5B6, Canada
References:
Abstract: We present here a probabilistic approach to the generation of new polynomials in two discrete variables. This extends our earlier work on the “classical” orthogonal polynomials in a previously unexplored direction, resulting in the discovery of an exactly soluble eigenvalue problem corresponding to a bivariate Markov chain with a transition kernel formed by a convolution of simple binomial and trinomial distributions. The solution of the relevant eigenfunction problem, giving the spectral resolution of the kernel, leads to what we believe to be a new class of orthogonal polynomials in two discrete variables. Possibilities for the extension of this approach are discussed.
Keywords: cumulative Bernoulli trials; multivariate Markov chains; $9-j$ symbols; transition kernel; Askey–Wilson polynomials; eigenvalue problem; trinomial distribution; Krawtchouk polynomials.
Received: September 15, 2008; in final form December 15, 2008; Published online December 19, 2008
Bibliographic databases:
Document Type: Article
MSC: 33C45; 60J05
Language: English
Citation: Michael R. Hoare, Mizan Rahman, “A Probablistic Origin for a New Class of Bivariate Polynomials”, SIGMA, 4 (2008), 089, 18 pp.
Citation in format AMSBIB
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\by Michael R.~Hoare, Mizan Rahman
\paper A~Probablistic Origin for a~New Class of Bivariate Polynomials
\jour SIGMA
\yr 2008
\vol 4
\papernumber 089
\totalpages 18
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  • This publication is cited in the following 29 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Symmetry, Integrability and Geometry: Methods and Applications
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