Analysis and generation of random vectors with copulas

Copulas are used in finance and insurance for modeling stochastic dependency. They comprehend the entire dependence structure, not only the correlations. Here they are estimated from measured samples of random vectors. The copula and the marginal distributions of the vector elements define a multivariate distribution of the sample which can be used to generate random vectors with this distribution. This can be applied as well to time series. A programmed algorithm is proposed. It is fast and allows for random vectors with high dimension, for example 100.