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Multiple Time Scale Analysis of Hierarchically Interacting Systems

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Stochastic Processes

Abstract

A hierarchically interacting stochastic model is introduced and its long time behavior is identified by multiple time scale analysis and an associated interaction chain.

Research supported by NSERC.

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References

  1. Cox, J.T. and Greven, A. (1991). Ergodic theorems for infinite systems of locally interacting diffusions, SFB Preprint no. 645, Heidelberg.

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  4. Dawson, D.A. and Greven, A. (1991). Hierarchical models of interacting diffusions: multiple time scale phenomena, phase transition and pattern of cluster-formation, SFB Preprint 648, Heidelberg.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Statistics, Carleton University, Ottawa, Canada, K1S 5B6

    Donald A. Dawson

  2. Institut für Mathematische Stochastik, Lotzestr. 13, 3400, Göttingen, FR Germany

    Andreas Greven

Authors
  1. Donald A. Dawson
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  2. Andreas Greven
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Editor information

Editors and Affiliations

  1. Department of Statistics, University of North Carolina, Chapel Hill, NC, 27599-3260, USA

    Stamatis Cambanis  & Pranab K. Sen  & 

  2. Indian Statistical Institute, 203, B.T. Road, 700035, Calcutta, India

    Jayanta K. Ghosh

  3. Indian Statistical Institute, 7, S.J.S. Sansanwal Marg, New Delhi, 110016, India

    Rajeeva L. Karandikar

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© 1993 Springer-Verlag New York, Inc.

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Dawson, D.A., Greven, A. (1993). Multiple Time Scale Analysis of Hierarchically Interacting Systems. In: Cambanis, S., Ghosh, J.K., Karandikar, R.L., Sen, P.K. (eds) Stochastic Processes. Springer, New York, NY. https://doi.org/10.1007/978-1-4615-7909-0_6

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  • DOI: https://doi.org/10.1007/978-1-4615-7909-0_6

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4615-7911-3

  • Online ISBN: 978-1-4615-7909-0

  • eBook Packages: Springer Book Archive

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