Computational methods applied to a skewed generalized normal family

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dc.contributor.author Bekker, Andriette, 1958-
dc.contributor.author Ferreira, Johannes Theodorus
dc.contributor.author Arashi, Mohammad
dc.contributor.author Rowland, B.W.
dc.date.accessioned 2019-01-15T11:23:10Z
dc.date.issued 2020
dc.description.abstract Some characteristics of the normal distribution may not be ideal to model in many applications. We develop a skew generalized normal (SGN) distribution by applying a skewing method to a generalized normal distribution, and study some meaningful statistical characteristics. Computational methods to approximate, and a well-constructed efficient computational approach to estimate these characteristics, are presented. A stochastic representation of this distribution is derived and numerically implemented. The skewing method is extended to the elliptical class resulting in a more general framework for skewing symmetric distributions. The proposed distribution is applied in a fitting context and to approximate particular binomial distributions. en_ZA
dc.description.department Statistics en_ZA
dc.description.embargo 2019-12-31
dc.description.librarian hj2019 en_ZA
dc.description.sponsorship The National Research Foundation, South Africa (Grant number: 91497; 109214; 102640). en_ZA
dc.description.uri http://www.tandfonline.com/loi/lssp20 en_ZA
dc.identifier.citation A. Bekker, J. T. Ferreira, M. Arashi & B. W. Rowland (2020): Computational methods applied to a skewed generalized normal family, Communications in Statistics - Simulation and Computation 49(11): 2930-2943, DOI: 10.1080/03610918.2018.1530785. en_ZA
dc.identifier.issn 0361-0918 (print)
dc.identifier.issn 1532-4141 (online)
dc.identifier.other 10.1080/03610918.2018.1530785
dc.identifier.uri http://hdl.handle.net/2263/68149
dc.language.iso en en_ZA
dc.publisher Taylor and Francis en_ZA
dc.rights © 2018 Taylor & Francis Group, LLC. This is an electronic version of an article published in Communications in Statistics : Simulation and Computation, vol. 49, no. 11, pp. 2930-2943, 2020. doi : 10.1080/03610918.2018.1530785. Communications in Statistics : Simulation and Computation is available online at : http://www.tandfonline.comloi/lssp20. en_ZA
dc.subject Approximating binomial distribution en_ZA
dc.subject Skew-normal en_ZA
dc.subject Stochastic representation en_ZA
dc.subject Computational methods en_ZA
dc.subject Symmetric distributions en_ZA
dc.subject Statistical characteristics en_ZA
dc.subject Generalized normal distribution en_ZA
dc.subject Binomial distribution en_ZA
dc.subject Transport properties en_ZA
dc.subject Stochastic systems en_ZA
dc.subject Normal distribution en_ZA
dc.subject Skew generalized normal (SGN) en_ZA
dc.title Computational methods applied to a skewed generalized normal family en_ZA
dc.type Postprint Article en_ZA


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