The motivation for this question is producing a distribution that produces the gender and age of an individual when the distribution of ages depends on gender.
Suppose I want a distribution which, when RandomVariate is applied to it, produces two values. The first value it produces is either 0 or 1 and the second value it produces is some real value between 0 and 65. But the second value is correlated with the first. By way of example, it might be the case that when the first value is 0, the second value tends to be lower than the when the first value is 1. I want the end product to be a distribution, so that one could apply things such as CDF to it.
Obviously, the gender distribution can be modeled as a BernoulliDistribution. And, as it happens I know how to model the age distribution conditioned on the person being a male and the age distribution conditioned on the person being a female. But how do I put them together? I've looked at CopulaDistribution and, while conceptually it might be appropriate, I don't see the kind of kernel I would need.
I have the feeling I am being stupid and that there is some obvious and elegant representation of this situation, but, at the moment, it escapes me. Help appreciated.