Farlie, "The performance of some correlation coefficients for a general
bivariate distribution," Biometrika, vol.
[17] have used the Macdonald distribution to construct a new
bivariate distribution which they call Macdonald-gamma distribution.
A bivariate copula is a
bivariate distribution function with both univariate margins distributed as U (0,1).
(26) The market skewness parameter is estimated simultaneously with the individual stock's skewness parameter and the single degrees of freedom parameter for the
bivariate distribution. Ideally we would prefer to estimate the entire multivariate (3518 dimensions) skew-t distribution simultaneously and thereby get one set of parameters for the market portfolio.
The Clayton copula can be used in this study to construct the
bivariate distribution of drought severity and duration.
Therefore, to the best of the authors' knowledge an analysis of the general
bivariate distribution Nakagami-lognormal with correlated both fading and shadowing and arbitrary fading parameters is novel in the literature.
Nevertheless, homogeneity was achieved in the
bivariate distribution in the three data sets from each of the measuring methods (i.e.
Then [rho] [member of] I and [t.sub.p,v] define the
bivariate distribution function corresponding to [t.sub.v]: