El-Bassiouny, A. H. and Jones, M. C.
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|DOI (Digital Object Identifier) Link:||https://doi.org/10.1007/s10260-008-0103-y|
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The classical bivariate F distribution arises from ratios of chi-squared random variables with common denominators. A consequent disadvantage is that its univariate F marginal distributions have one degree of freedom parameter in common. In this paper, we add a further independent chi-squared random variable to the denominator of one of the ratios and explore the extended bivariate F distribution, with marginals on arbitrary degrees of freedom, that results. Transformations linking F, beta and skew t distributions are then applied componentwise to produce bivariate beta and skew t distributions which also afford marginal (beta and skew t) distributions with arbitrary parameter values. We explore a variety of properties of these distributions and give an example of a potential application of the bivariate beta distribution in Bayesian analysis.
|Item Type:||Journal Article|
|Copyright Holders:||2008 Springer-Verlag|
|Extra Information:||The original publication is available at www.springerlink.com.|
|Keywords:||chi-squared distribution; positive dependence; transformation|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Depositing User:||Sarah Frain|
|Date Deposited:||10 Aug 2010 11:12|
|Last Modified:||07 Oct 2016 08:15|
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