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Simulation of polyhedral convex contoured distributions

Author

Listed:
  • Wolf-Dieter Richter

    (University of Rostock)

  • Kay Schicker

    (University of Rostock)

Abstract

In low dimensions, the relatively easily implementable acceptance-rejection method for generating polyhedral convex contoured uniform distributions is compared to more sophisticated particular methods from the literature, and applied to drug combination studies. Based upon a stochastic representation, the method is extended to the general class of polyhedral convex contoured distributions of known dimension. Based upon a geometric measure representation, an algorithm for simulating corresponding probabilities of rather arbitrary random events is derived.

Suggested Citation

  • Wolf-Dieter Richter & Kay Schicker, 2017. "Simulation of polyhedral convex contoured distributions," Journal of Statistical Distributions and Applications, Springer, vol. 4(1), pages 1-19, December.
  • Handle: RePEc:spr:jstada:v:4:y:2017:i:1:d:10.1186_s40488-017-0055-6
    DOI: 10.1186/s40488-017-0055-6
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    References listed on IDEAS

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    1. Balkema, A.A. & Embrechts, P. & Nolde, N., 2010. "Meta densities and the shape of their sample clouds," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1738-1754, August.
    2. Henschel, V. & Richter, W. -D., 2002. "Geometric Generalization of the Exponential Law," Journal of Multivariate Analysis, Elsevier, vol. 81(2), pages 189-204, May.
    3. Tian, Guo-Liang & Fang, Hong-Bin & Tan, Ming & Qin, Hong & Tang, Man-Lai, 2009. "Uniform distributions in a class of convex polyhedrons with applications to drug combination studies," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1854-1865, September.
    4. Fang, Kai-Tai & Yang, Zhen-Hai, 2000. "On uniform design of experiments with restricted mixtures and generation of uniform distribution on some domains," Statistics & Probability Letters, Elsevier, vol. 46(2), pages 113-120, January.
    Full references (including those not matched with items on IDEAS)

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