IDEAS home Printed from https://ideas.repec.org/a/wly/apsmbi/v35y2019i2p376-393.html
   My bibliography  Save this article

Mode hunting through active information

Author

Listed:
  • Daniel Andrés Díaz‐Pachón
  • Juan Pablo Sáenz
  • J. Sunil Rao
  • Jean‐Eudes Dazard

Abstract

We propose a new method to find modes based on active information. We develop an algorithm called active information mode hunting (AIMH) that, when applied to the whole space, will say whether there are any modes present and where they are. We show AIMH is consistent and, given that information increases where probability decreases, it helps to overcome issues with the curse of dimensionality. The AIMH also reduces the dimensionality with no resource to principal components. We illustrate the method in three ways: with a theoretical example (showing how it performs better than other mode hunting strategies), a real dataset business application, and a simulation.

Suggested Citation

  • Daniel Andrés Díaz‐Pachón & Juan Pablo Sáenz & J. Sunil Rao & Jean‐Eudes Dazard, 2019. "Mode hunting through active information," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(2), pages 376-393, March.
    • Handle: RePEc:wly:apsmbi:v:35:y:2019:i:2:p:376-393
    DOI: 10.1002/asmb.2430
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asmb.2430
    Download Restriction: no
    File URL: https://libkey.io/10.1002/asmb.2430?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Díaz–Pachón, Daniel Andrés & Sáenz, Juan Pablo & Rao, J. Sunil, 2020. "Hypothesis testing with active information," Statistics & Probability Letters, Elsevier, vol. 161(C).

    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:wly:apsmbi:v:35:y:2019:i:2:p:376-393. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1526-4025 .

    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.