A new family of positive quadrant dependent bivariate distributions
AbstractPositive quadrant dependence (PQD) is a notion of bivariate dependence between two positively dependent random variables. Starting from the uniform representation of the Farlie-Gumbel-Morgenstern bivariate distribution, we derive and study a family of continuous bivariate distributions that possesses the PQD property. In particular, we show that this new parametric family of distributions can be ordered in the so-called "PQD order".
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 46 (2000)
Issue (Month): 4 (February)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Nelsen, Roger B., 1992. "On measures of association as measures of positive dependence," Statistics & Probability Letters, Elsevier, vol. 14(4), pages 269-274, July.
- I. Bairamov & S. Kotz & M. Bekci, 2001. "New generalized Farlie-Gumbel-Morgenstern distributions and concomitants of order statistics," Journal of Applied Statistics, Taylor and Francis Journals, vol. 28(5), pages 521-536.
- Fischer, Matthias J. & Klein, Ingo, 2004. "Constructing symmetric generalized FGM copulas by means of certain univariate distributions," Discussion Papers 61/2004, Friedrich-Alexander-University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
- Lin, G.D. & Huang, J.S., 2010. "A note on the maximum correlation for Baker's bivariate distributions with fixed marginals," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2227-2233, October.
- Arjun Gupta & Johanna Orozco-Castañeda & Daya Nagar, 2011. "Non-central bivariate beta distribution," Statistical Papers, Springer, vol. 52(1), pages 139-152, February.
- Rodríguez-Lallena, José Antonio & Úbeda-Flores, Manuel, 2004. "A new class of bivariate copulas," Statistics & Probability Letters, Elsevier, vol. 66(3), pages 315-325, February.
- Cuadras, Carles M. & Cuadras, Daniel, 2008. "Eigenanalysis on a bivariate covariance kernel," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2497-2507, November.
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