• DocumentCode
    3270514
  • Title

    Fitting mixture importance sampling distributions via improved cross-entropy

  • Author

    Brereton, Tim J. ; Chan, Joshua C C ; Kroese, Dirk P.

  • Author_Institution
    Dept. of Math., Univ. of Queensland, Brisbane, QLD, Australia
  • fYear
    2011
  • fDate
    11-14 Dec. 2011
  • Firstpage
    422
  • Lastpage
    428
  • Abstract
    In some rare-event settings, exponentially twisted distributions perform very badly. One solution to this problem is to use mixture distributions. However, it is difficult to select a good mixture distribution for importance sampling. We here introduce a simple adaptive method for choosing good mixture importance sampling distributions.
  • Keywords
    entropy; importance sampling; statistical distributions; adaptive method; cross-entropy; mixture importance sampling distribution fitting; rare-event probability; Algorithm design and analysis; Australia; Educational institutions; Estimation; Monte Carlo methods; Numerical models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference (WSC), Proceedings of the 2011 Winter
  • Conference_Location
    Phoenix, AZ
  • ISSN
    0891-7736
  • Print_ISBN
    978-1-4577-2108-3
  • Electronic_ISBN
    0891-7736
  • Type

    conf

  • DOI
    10.1109/WSC.2011.6147769
  • Filename
    6147769
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3270514