IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/112480.html
   My bibliography  Save this paper

Exploiting disagreement between high-dimensional variable selectors for uncertainty visualization

Author

Listed:
  • Yuen, Christine
  • Fryzlewicz, Piotr

Abstract

We propose combined selection and uncertainty visualizer (CSUV), which visualizes selection uncertainties for covariates in high-dimensional linear regression by exploiting the (dis)agreement among different base selectors. Our proposed method highlights covariates that get selected the most frequently by the different base variable selection methods on subsampled data. The method is generic and can be used with different existing variable selection methods. We demonstrate its performance using real and simulated data. The corresponding R package CSUV is at https://github.com/christineyuen/CSUV, and the graphical tool is also available online via https://csuv.shinyapps.io/csuv.

Suggested Citation

  • Yuen, Christine & Fryzlewicz, Piotr, 2022. "Exploiting disagreement between high-dimensional variable selectors for uncertainty visualization," LSE Research Online Documents on Economics 112480, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:112480
    as

    Download full text from publisher

    File URL: http://eprints.lse.ac.uk/112480/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    high-dimensional data; variable selection; uncertainty visualization;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ehl:lserod:112480. 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: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    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.