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The supremum of Gaussian processes with a constant variance
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  • Published: May 1989

The supremum of Gaussian processes with a constant variance

  • Michel Weber1 

Probability Theory and Related Fields volume 81, pages 585–591 (1989)Cite this article

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  • 14 Citations

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Summary

We obtain an estimate of the distribution of the large values of the supremum of a sample bounded Gaussian process having a constant variance. This estimate uses the entropy function of the parameter space endowed, as usual, with the pseudo-metric induced by the L 2-norm of the increments of the process.

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References

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Authors and Affiliations

  1. UER de Mathématiques et Informatique, Université Louis Pasteur, 7, Rue René Descartes, F-67084, Strasbourg, Cedex, France

    Michel Weber

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  1. Michel Weber
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Cite this article

Weber, M. The supremum of Gaussian processes with a constant variance. Probab. Th. Rel. Fields 81, 585–591 (1989). https://doi.org/10.1007/BF00367305

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  • Received: 04 December 1987

  • Issue Date: May 1989

  • DOI: https://doi.org/10.1007/BF00367305

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Keywords

  • Entropy
  • Parameter Space
  • Stochastic Process
  • Probability Theory
  • Statistical Theory
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