IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-13-2971-5_2.html
   My bibliography  Save this book chapter

Sequential Monte Carlo

In: Monte Carlo Methods

Author

Listed:
  • Adrian Barbu

    (Florida State University, Department of Statistics)

  • Song-Chun Zhu

    (University of California, Los Angeles, Departments of Statistics and Computer Science)

Abstract

Sequential Monte Carlo Sequential Monte Carlo (SMC) is used when the distribution of interest is one-dimensional or multi-dimensional and factorizable. If f(x) denotes the true probability distribution function controlling a process and π(x) denotes a target probability distribution based on a model, then the goal is to find a model to make the target density function π(x) converge to f(x). In order to find this model, a known, trial probability density g(x) may be used. In this chapter several concepts related to the selection of g(x) for SMC are covered including sample weighting and importance sampling. Applications covered include self-avoiding walks, Parzen windows, ray tracing, particle filtering, and glossy highlights. The chapter ends with a discussion of Monte Carlo Tree Search.

Suggested Citation

  • Adrian Barbu & Song-Chun Zhu, 2020. "Sequential Monte Carlo," Springer Books, in: Monte Carlo Methods, chapter 2, pages 19-48, Springer.
    • Handle: RePEc:spr:sprchp:978-981-13-2971-5_2
    DOI: 10.1007/978-981-13-2971-5_2
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-981-13-2971-5_2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.