IDEAS home Printed from https://ideas.repec.org/a/ids/injdan/v11y2019i1p29-57.html
   My bibliography  Save this article

A comprehensive comparison of algorithms for the statistical modelling of non-monotone relationships via isotonic regression of transformed data

Author

Listed:
  • Simone Fiori

Abstract

The paper treats the problem of nonlinear, non-monotonic regression of bivariate datasets by means of a statistical regression method known from the literature. In particular, the present paper introduces two new regression methods and illustrates the results of a comprehensive comparison of the performances of the best two previous methods, the two new methods introduced here and as much as ten standard regression methods known from the specialised literature. The comparison is performed over nine different datasets, ranging from electrocardiogram data to text analysis data, by means of four figures of merit, that include regression precision as well as runtime.

Suggested Citation

  • Simone Fiori, 2019. "A comprehensive comparison of algorithms for the statistical modelling of non-monotone relationships via isotonic regression of transformed data," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 11(1), pages 29-57.
    • Handle: RePEc:ids:injdan:v:11:y:2019:i:1:p:29-57
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=96617
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:injdan:v:11:y:2019:i:1:p:29-57. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=282 .

    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.