الفهرس 
Bivariate cdf propertiesOnly 14 pages are availabe for public view
 |  | from | 136 |  |  |
| | | from | 136 | | |
Abstract
Copulas are mathematical objects that fully capture the dependence structure among random variables and thus offer a great deal of flexibility in building multivariate stochastic models. They have widely
use in credit models risk aggregation portfolio selection insurance reliability disinterestedness in copulas arise from several prospects econometricians often possess more information about distributions of related variables than their joint distribution. The approachability is a useful method for pediment joint distributions given marginalization distributions especially when the variables are not normalization in a bivariate state copulas can be used to nonparametric measures of dependence for pairs of random variables are useful extensions and generalizations of approaches remodeling joint distributions and dependence that have appeared in literature