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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 SarabiaThis 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 AnalysisISSN
0167-9473Publisher
ElsevierExternal DOI
Issue
6Volume
56Page range
1880-1897Department affiliated with
- Business and Management Publications
Full text available
- No
Peer reviewed?
- Yes