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Rotational (and Other) Representations of Stochastic Matrices 

Authors: Steve Alpern a; V. S. Prasad b
Affiliations:   a Department of Mathematics, London School of Economics, London, United Kingdom
b Department of Mathematics, University of Massachusetts Lowell, Lowell, Massachusetts, USA
DOI: 10.1080/07362990701670209
Publication Frequency: 6 issues per year
Published in: journal Stochastic Analysis and Applications, Volume 26, Issue 1 January 2008 , pages 1 - 15
Formats available: HTML (English) : PDF (English)
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Abstract

Joel E. Cohen (Annals of Probability, 9(1981):899-901) conjectured that any stochastic matrix P = lcubpi, jrcub could be represented by some circle rotation f in the following sense: For some partition lcubSircub of the circle into sets consisting of finite unions of arcs, we have (*)pi, j = μ(f(Si) ∩ Sj)/μ(Si), where μ denotes arc length. In this article we show how cycle decomposition techniques originally used (Alpern, Annals of Probability, 11(1983):789-794) to establish Cohen's conjecture can be extended to give a short simple proof of the Coding Theorem, that any mixing (that is, PN > 0 for some N) stochastic matrix P can be represented (in the sense of * but with Si merely measurable) by any aperiodic measure preserving bijection (automorphism) of a Lesbesgue probability space. Representations by pointwise and setwise periodic automorphisms are also established. While this article is largely expository, all the proofs, and some of the results, are new.
Keywords: Cycle decomposition; Rotational representation; Stochastic matrix
Mathematics Subject Classification: Primary 60J10; Secondary 15A51
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