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n-Kernel orthogonal polynomials on the Dirichlet, Dirichlet-Multinomial, Poisson-Dirichlet and Ewens sampling distributions, and positive-definite sequences

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Griffiths, Robert C. and Spanò, Dario (2010) n-Kernel orthogonal polynomials on the Dirichlet, Dirichlet-Multinomial, Poisson-Dirichlet and Ewens sampling distributions, and positive-definite sequences. Working Paper. University of Warwick. Centre for Research in Statistical Methodology, Coventry.

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Abstract

We consider a multivariate version of the so-called Lancaster problem of characterizing canonical correlation coe±cients of symmetric bivariate distributions with identical marginals and orthogonal polynomial expansions. The marginal distributions examined in this paper are the Dirichlet and the Dirichlet-Multinomial distribution, respectively on the continuous and the N-discrete d-dimensional simplex. Their infinite-dimensional limit distributions, respectively the Poisson-Dirichlet distribution and the Ewens' sampling formula, are considered as well. We study in particular the possibility of mapping canonical correlations on the d-dimensional continuous simplex (i) to canonical correlation sequences on the d + 1-dimensional simplex and/or (ii) to canonical correlations on the discrete simplex, and viceversa. Driven by this motivation, the first half of the paper is devoted to providing a full characterization and probabilistic interpretation of |n|-orthogonal polynomial kernels (i.e. sums of products of orthogonal polynomials of the same degree |n|) with respect to the mentioned marginal distributions. Orthogonal polynomial kernels are important to overcome some non-uniqueness di±culties arising when dealing with multivariate orthogonal (or bi-orthogonal) polynomials.We estab- lish several identities and some integral representations which are multivariate extensions of important results known for the case d = 2 since the 1970's. These results, along with a common interpretation of the mentioned kernels in terms of dependent Polya urns, are shown to be key features leading to several non-trivial solutions to Lancaster's problem, many of which can be extended naturally to the limit as d -> ∞.

Item Type: Working or Discussion Paper (Working Paper)
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH): Multivariate analysis, Correlation (Statistics), Marginal distributions, Kernel functions
Series Name: Working papers
Publisher: University of Warwick. Centre for Research in Statistical Methodology
Place of Publication: Coventry
Date: 2010
Volume: Vol.2010
Number: No.7
Number of Pages: 40
Status: Not Peer Reviewed
Access rights to Published version: Open Access
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URI: http://wrap.warwick.ac.uk/id/eprint/35071

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