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Markov Chains and Multiple Orthogonality

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arxiv 2304.04414 v1 pith:ZFIDYY5R submitted 2023-04-10 math.PR math.CA

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keywords diagonalhessenbergmultiplestochastictetrachainsmarkovmatrices
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In this work we survey on connections of Markov chains and the theory of multiple orthogonality. Here we mainly concentrate on give a procedure to generate stochastic tetra diagonal Hessenberg matrices, coming from some specific families of multiple orthogonal, such as the ones of Jacobi--Pi\~neiro and Hypergeometric Lima--Loureiro. We show that associated with a positive tetra diagonal nonnegative bounded Hessenberg matrix we can construct two stochastic tetra diagonal ones. These two stochastic tridiagonal nonnegative Hessenberg matrices are shown to be, enlightened by the Poincar\'e theorem, limit transpose of each other.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Mixed Multiple Orthogonal Laurent Polynomials on the Unit Circle

    math.CA 2024-11 conditional novelty 7.0 of 10

    A Gauss-Borel factorization of a rectangular moment matrix yields the first systematic framework for mixed multiple orthogonal Laurent polynomials on the unit circle, with Christoffel and Geronimus perturbation formulas.

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