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El-Bassiouny, A. H. and Jones, M. C.
(2009).
DOI: https://doi.org/10.1007/s10260-008-0103-y
Abstract
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.
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About
- Item ORO ID
- 22505
- Item Type
- Journal Item
- ISSN
- 1618-2510
- Extra Information
- The original publication is available at www.springerlink.com.
- Keywords
- chi-squared distribution; positive dependence; transformation
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Copyright Holders
- © 2008 Springer-Verlag
- Depositing User
- Sarah Frain