I try to understand the basic idea of copulas, however I am still struggling and hope that someone can help me.
I understood that in general a copula is a function which links several marginal distributions to a multivariate distribution. Turning this idea around: if the joint probability function H() is known, I can extract the copula. However, what I do not understand is the intuition behind the step marked by the red arrow. What is the logic behind that? My problem is also to understand the inverse cumulative density function in this context. Perhaps someone has an illustrative example to make this step more clear to me as a non-mathematician.