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Computational Statistics pp 257–262Cite as

Stochastic Simulation in Mixed Graphical Association Models

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Abstract

The application of stochastic simulation to mixed graphical association models enables us not only to estimate the marginal probabilities, means and variances of the variables, but also to estimate the marginal densities of continuous variables.

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References

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Author information

Authors and Affiliations

  1. Department of Mathematics and Statistics, University of Edinburgh, James Clerk Maxwell Building, Edinburgh, EH9 3JZ, UK

    M. J. Brewer & C. G. G. Aitken

  2. Department of Computer Science, Heriot-Watt University, Riccarton, Edinburgh, EH14 4AS, UK

    Z. Luo & A. Gammerman

Authors
  1. M. J. Brewer
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  2. C. G. G. Aitken
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  3. Z. Luo
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  4. A. Gammerman
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Editor information

Editors and Affiliations

  1. Groupe de Statistique, University of Neuchâtel, Pierre-à-Mazel 7, CH-2000, Neuchâtel, Switzerland

    Yadolah Dodge (Professor of Statistics and Operations Research) (Professor of Statistics and Operations Research)

  2. Lancaster University, GB-Lancaster, LA1 4YE, Great Britain

    Joe Whittaker (Professor of Mathematics) (Professor of Mathematics)

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© 1992 Springer-Verlag Berlin Heidelberg

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Cite this paper

Brewer, M.J., Aitken, C.G.G., Luo, Z., Gammerman, A. (1992). Stochastic Simulation in Mixed Graphical Association Models. In: Dodge, Y., Whittaker, J. (eds) Computational Statistics. Physica, Heidelberg. https://doi.org/10.1007/978-3-662-26811-7_34

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  • DOI: https://doi.org/10.1007/978-3-662-26811-7_34

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-662-26813-1

  • Online ISBN: 978-3-662-26811-7

  • eBook Packages: Springer Book Archive

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