Determing the probability distribution of coefficients given a particular value

[jessegrabowski]

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Samples from Conditional Posterior Distribution

Let us consider the following Hierarchical Bayesian model: w \sim\ Beta(20, 20) K = 6 a = w * (K - 2) + 1 b = (1 - w) * (K - 2) + 1 theta \sim\ Beta(a, b) y \sim\ Bern(theta) The above is the example of figure 9.3 in the book Doing Bayesian Data Analysis by John Kruschke. I use the pymc3 to construct the model as follows: import numpy as np import pymc3 as pm import arviz as az K = 6 D = np.array([1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0]) with pm.Model() as mdl: w = pm.Beta('w', alpha…