Bivariate distributions characterized by one family of conditionals and conditional percentile or mode functions
It is well known that full knowledge of all conditional distributions will typically serve to completely characterize a bivariate distribution. Partial knowledge will often suffice. For example, knowledge of the conditional distribution of X given Y and the conditional mean of Y given X is often adequate to determine the joint distribution of X and Y. In this paper, we investigate the extent to which a conditional percentile function or a conditional mode function (of Y given X), together with knowledge of the conditional distribution of X given Y will determine the joint distribution. Finally, using this methodology a new characterization of the classical bivariate normal distribution is given.
Year of publication: |
2008
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Authors: | Arnold, Barry C. ; Castillo, Enrique ; Sarabia, José María |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 99.2008, 7, p. 1383-1392
|
Publisher: |
Elsevier |
Keywords: | 62H05 60E05 Conditional specification Farley-Gumbel-Morgenstern distribution Gumbel's bivariate logistic distribution Normal characterization Cauchy conditionals |
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