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Proceedings of the American Mathematical Society

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Markov process representations of general stochastic processes


Author: Dudley Paul Johnson
Journal: Proc. Amer. Math. Soc. 24 (1970), 735-738
MSC: Primary 60.62
DOI: https://doi.org/10.1090/S0002-9939-1970-0261690-0
MathSciNet review: 0261690
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Abstract: In this paper we show that any separable stochastic process on a compact metric space can be derived from a temporally homogeneous Markov process on the extreme points of a compact convex set of measures.


References [Enhancements On Off] (What's this?)

  • [1] N. Dunford and J. Schwartz, Linear operators. I: General theory, Pure and Appl. Math., vol. 7, Interscience, New York, 1958. MR 22 #8302. MR 0117523 (22:8302)
  • [2] P. A. Meyer, Probability and potentials, Blaisdell, Waltham, Mass., 1966. MR 34 #5119. MR 0205288 (34:5119)

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Additional Information

DOI: https://doi.org/10.1090/S0002-9939-1970-0261690-0
Keywords: Stochastic process, temporally homogeneous Markov process, extreme points, Choquet's Theorem
Article copyright: © Copyright 1970 American Mathematical Society

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