Random doubly stochastic tridiagonal matrices |
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Authors: | Persi Diaconis Philip Matchett Wood |
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Affiliation: | 1. Department of Statistics, Stanford University, Stanford, California 94305;2. Department of Mathematics, Stanford University, Stanford, California 94305;3. Department of Mathematics, University of Wisconsin, Madison, Wisconsin 53706‐1388 |
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Abstract: | Let begin{align*}{mathcal T}end{align*}n be the compact convex set of tridiagonal doubly stochastic matrices. These arise naturally in probability problems as birth and death chains with a uniform stationary distribution. We study ‘typical’ matrices T∈ begin{align*}{mathcal T}end{align*}n chosen uniformly at random in the set begin{align*}{mathcal T}end{align*}n. A simple algorithm is presented to allow direct sampling from the uniform distribution on begin{align*}{mathcal T}end{align*}n. Using this algorithm, the elements above the diagonal in T are shown to form a Markov chain. For large n, the limiting Markov chain is reversible and explicitly diagonalizable with transformed Jacobi polynomials as eigenfunctions. These results are used to study the limiting behavior of such typical birth and death chains, including their eigenvalues and mixing times. The results on a uniform random tridiagonal doubly stochastic matrices are related to the distribution of alternating permutations chosen uniformly at random.© 2012 Wiley Periodicals, Inc. Random Struct. Alg., 42, 403–437, 2013 |
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Keywords: | Markov chain birth and death chain cutoff phenomenon random matrix |
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