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A Quasi Monte Carlo Approach to Piecewise Linear Markov Approximations of Markov Operators

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  • Ding Jiu

    (1. Department of Mathematics, The University of Southern Mississippi, Hattiesburg, MS 39406-5045, USA.)

  • Mao Dong

    (2. Institute of Systems Science, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing 100080, China.)

  • Zhou Aihui

    (3. Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing 100080, China.)

Abstract

In this paper, we address the computational issue of approximating Markov operators which are widely used in the stochastic study of chaotic dynamical systems. We will concentrate on a quasi Monte Carlo implementation of piecewise linear Markov approximations that preserve the Markov structure.

Suggested Citation

  • Ding Jiu & Mao Dong & Zhou Aihui, 2003. "A Quasi Monte Carlo Approach to Piecewise Linear Markov Approximations of Markov Operators," Monte Carlo Methods and Applications, De Gruyter, vol. 9(4), pages 295-309, December.
    • Handle: RePEc:bpj:mcmeap:v:9:y:2003:i:4:p:295-309:n:1
    DOI: 10.1515/156939603322601932
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    References listed on IDEAS

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    1. J. Ding & Z. Wang, 2001. "Parallel Computation of Invariant Measures," Annals of Operations Research, Springer, vol. 103(1), pages 283-290, March.
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