IDEAS home Printed from https://ideas.repec.org/a/wly/jjmath/v2022y2022i1n1144296.html

Regression Coefficient Derivation via Fractional Calculus Framework

Author

Listed:
  • Muath Awadalla
  • Yves Yannick Yameni Noupoue
  • Yucel Tandogdu
  • Kinda Abuasbeh

Abstract

This study focuses on deriving coefficients of a simple linear regression model and a quadratic regression model using fractional calculus. The work has proven that there is a smooth connection between fractional operators and classical operators. Moreover, it has also been shown that the least squares method is classically used to obtain coefficients of linear and quadratic models that are viewed as special cases of the more general fractional derivative approach which is proposed.

Suggested Citation

  • Muath Awadalla & Yves Yannick Yameni Noupoue & Yucel Tandogdu & Kinda Abuasbeh, 2022. "Regression Coefficient Derivation via Fractional Calculus Framework," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:jjmath:v:2022:y:2022:i:1:n:1144296
    DOI: 10.1155/2022/1144296
    as

    Download full text from publisher

    File URL: https://doi.org/10.1155/2022/1144296
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/1144296?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
    ---><---

    References listed on IDEAS

    as
    1. Areeg Abdalla & James Buckley, 2008. "Monte Carlo Methods In Fuzzy Non-Linear Regression," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 4(02), pages 123-141.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      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:jjmath:v:2022:y:2022:i:1:n:1144296. 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.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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://onlinelibrary.wiley.com/journal/1469 .

      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.