Generalized beta-generated distributions

Carol Alexander, Gauss M. Cordeiro, Edwin M.M. Ortega and José María Sarabia ()

Computational Statistics & Data Analysis, 2012, vol. 56, issue 6, 1880-1897

Abstract: 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.

Keywords: Entropy; Exponentiated; Kumaraswamy; Kurtosis; McDonald; Minimax; Skewness (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (38)

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Related works:
Working Paper: Generalized Beta-Generated Distributions (2011)
Working Paper: Generalized Beta-Generated Distributions (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:56:y:2012:i:6:p:1880-1897

DOI: 10.1016/j.csda.2011.11.015

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