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    Estimation of parameters in mean-reverting stochastic systems

    198775_113525_317059.pdf (2.206Mb)
    Access Status
    Open access
    Authors
    Tian, T.
    Zhou, Y.
    Wu, Yong Hong
    Ge, X.
    Date
    2014
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Tian, Tianhai and Zhou, Yanli and Wu, Yonghong and Ge, Xiangyu. 2014. Estimation of parameters in mean-reverting stochastic systems. Mathematical Problems in Engineering. 2014: (Article ID 317059): pp. 1-8.
    Source Title
    Mathematical Problems in Engineering
    DOI
    10.1155/2014/317059
    ISSN
    1024123X
    Remarks

    This article is published under the Open Access publishing model and distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/. Please refer to the licence to obtain terms for any further reuse or distribution of this work.

    URI
    http://hdl.handle.net/20.500.11937/31895
    Collection
    • Curtin Research Publications
    Abstract

    Stochastic differential equation (SDE) is a very important mathematical tool to describe complex systems in which noise plays an important role. SDE models have been widely used to study the dynamic properties of various nonlinear systems in biology, engineering, finance, and economics, as well as physical sciences. Since a SDE can generate unlimited numbers of trajectories, it is difficult to estimate model parameters based on experimental observations which may represent only one trajectory of the stochastic model. Although substantial research efforts have been made to develop effective methods, it is still a challenge to infer unknown parameters in SDE models from observations that may have large variations. Using an interest rate model as a test problem, in this work we use the Bayesian inference and Markov Chain Monte Carlo method to estimate unknown parameters in SDE models.

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