Having problems defining random function for custom distribution with mixture of observed and random variables

You already have alpha and beta individual from the posterior trace. The question is to generate random sample of S according to the Density function.
If a specific random generation algorithm is not known, I guess you can always implement a reject sampler or an important sampler. There is no example for it in pymc3, so if you got something working please share with us :wink: