# quantile surface of a mulitvariate distribution made of multiplication of marginal distributions assuming independence

How to perform quantile regression in a more elegant fashion?

As discussed above, quantSheets() can only deal with one explanatory variable for computing quantile curves.

In reality, many distributions are multivariate. If one can assume the explanatory variables are independent of each other, then the join distribution of these variables is just the multiplication of the marginal distributions wrt to each explanatory variable.

But it is not clear to me how to estimate the quantile surface for such a joint distribution. Does anybody know a solution to this problem?