• DocumentCode
    843434
  • Title

    Guest Editors´ Introduction: Monte Carlo Methods

  • Author

    Beichl, Isabel ; Sullivan, Francis

  • Author_Institution
    National Institute of Standards and Technology
  • Volume
    8
  • Issue
    2
  • fYear
    2006
  • Firstpage
    7
  • Lastpage
    8
  • Abstract
    The term Monte Carlo method stands for any member of a very large class of computational methods that use randomness to generate "typical" instances of a problem under investigation. Typical instances are generated because it\´s impractical or even impossible to generate all instances. A set of typical instances is supposed to help us learn something about a problem of interest. Most of the time, Monte Carlo works amazingly well, but when used blindly, with no firm basis in theory, it can yield some very strange results or run for many, many hours and yield nothing. One of the triumphs of the modern period in Monte Carlo methods has been a dramatic improvement in our understanding of how to speed up the computation and how to know when the method will work.
  • Keywords
    Markov chains; Monte Carlo; algorithm; randomness; Acceleration; Convergence; Game theory; Kinetic theory; Monte Carlo methods; NIST; Needles; Probability distribution; Terminology; Markov chains; Monte Carlo; algorithm; randomness;
  • fLanguage
    English
  • Journal_Title
    Computing in Science & Engineering
  • Publisher
    ieee
  • ISSN
    1521-9615
  • Type

    jour

  • DOI
    10.1109/MCSE.2006.27
  • Filename
    1599368