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PyMC3 approach to solve Bayesian coin flip example
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| import pymc3 as pm | |
| with pm.Model() as coinflip: | |
| which_coin = pm.Bernoulli('which_coin', 0.5) | |
| theta_biased = pm.Uniform('theta_biased', 0, 1) | |
| p = pm.math.switch(which_coin > 0.5, 0.5, theta_biased) | |
| heads = pm.Binomial('heads', n=2, p=p, observed=2) | |
| coin_trace = pm.sample(5000, tune=2500) | |
| pm.traceplot(coin_trace); | |
| print('p(coin=fair|HH)={}'.format( | |
| coin_trace['which_coin'].mean() | |
| )) |
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