python - Making a custom probability distribution to draw random samples from in SciPy -


i'm looking sum arbitrary number of probabilistic distributions of things using montecarlo type simulation. i'd randomly sample continuous distributions of , add them other random samples of other continuous distributions, getting probability distribution combination. distributions empirical - aren't function in form of p99 = 2.4, p90 = 7.12, p50 = 24.53, p10 = 82.14 , on (in reality there bunch of points). distributions more or less lognormal, approximating them lognormal fine, if that's necessary. how enter scipy's lognorm function? or other way in scipy, or python in general?

i hope it's clear i'm trying do. lot, alex

it looks have histogram of probability density. 1 thing can use inverse transform sampling empirical distribution.

as alternative, if expect functional form of distribution (lognorm or other one), can try fitting data corresponding functional form.


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