University of Sussex
Browse

File(s) not publicly available

Generalized beta-generated distributions

journal contribution
posted on 2023-06-08, 12:23 authored by Carol AlexanderCarol Alexander, Gauss M Cordeiro, Edwin M M Ortega, José María Sarabia
This article introduces generalized beta-generated (GBG) distributions. Sub-models include all classical beta-generated, Kumaraswamy-generated and exponentiated distributions. They are maximum entropy distributions under three intuitive conditions, which show that the classical beta generator skewness parameters only control tail entropy and an additional shape parameter is needed to add entropy to the centre of the parent distribution. This parameter controls skewness without necessarily differentiating tail weights. The GBG class also has tractable properties: we present various expansions for moments, generating function and quantiles. The model parameters are estimated by maximum likelihood and the usefulness of the new class is illustrated by means of some real data sets.

History

Publication status

  • Published

Journal

Computational Statistics and Data Analysis

ISSN

0167-9473

Publisher

Elsevier

Issue

6

Volume

56

Page range

1880-1897

Department affiliated with

  • Business and Management Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2012-09-11

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC