IDEAS home Printed from https://ideas.repec.org/a/hin/jnljps/7967345.html
   My bibliography  Save this article

Comparative Study between Generalized Maximum Entropy and Bayes Methods to Estimate the Four Parameter Weibull Growth Model

Author

Listed:
  • Saifaldin Hashim Kamar
  • Basim Shlaibah Msallam

Abstract

The Weibull growth model is an important model especially for describing the growth instability; therefore, in this paper, three methods, namely, generalized maximum entropy, Bayes, and maximum a posteriori, for estimating the four parameter Weibull growth model have been presented and compared. To achieve this aim, it is necessary to use a simulation technique to generate the samples and perform the required comparisons, using varying sample sizes (10, 12, 15, 20, 25, and 30) and models depending on the standard deviation (0.5). It has been shown from the computational results that the Bayes method gives the best estimates.

Suggested Citation

  • Saifaldin Hashim Kamar & Basim Shlaibah Msallam, 2020. "Comparative Study between Generalized Maximum Entropy and Bayes Methods to Estimate the Four Parameter Weibull Growth Model," Journal of Probability and Statistics, Hindawi, vol. 2020, pages 1-7, January.
  • Handle: RePEc:hin:jnljps:7967345
    DOI: 10.1155/2020/7967345
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/JPS/2020/7967345.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/JPS/2020/7967345.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2020/7967345?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
    ---><---

    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:hin:jnljps:7967345. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.