Hi, I’d like to compile a model that uses a Dirichlet distribution that takes a random variable as a parameter. I tried: import pymc3 as pm import numpy as np def sigmoid(x): return 1 / (1 + np.exp(-x)) with pm.Model() as model: x = pm.Normal("x") s = sigmoid(x) w = pm.Dirichlet.…

The correct syntax goes like this: import pymc3 as pm import theano.tensor as tt def sigmoid(x): return 1 / (1 + tt.exp(-x)) with pm.Model() as model: x = pm.Normal("x") s = sigmoid(x) w = pm.Dirichlet('w', a=tt.stack([1. - s, s]), shape=2) pm.Mixture("y", w, [pm.Normal.dist(mu…

Creating a Dirichlet distribution from a random variable

Questions

kpei November 16, 2017, 7:56pm 4

You can further condense the code through using pm.math.sigmoid rather than defining it manually

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Creating a Dirichlet distribution from a random variable

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