Distributions.jl: how to create a mixture of a scaled Beta distribution?

[empet]

If X\sim Beta(a,b), and c is a number in (0,1), then cX
isn’t Beta distributed. Hence your d is not a mixture of Beta distributions.
It works with just:

d = MixtureModel([0.5 * Beta(1, 1), 0.5 * Beta(2, 10)], [0.5, 0.5])