In [1]:

    

%matplotlib inline


    

In [2]:

    

import numpy as np
import pymc3 as pm
import seaborn as sns
import pandas as pd


    

    




Couldn't import dot_parser, loading of dot files will not be possible.






    




:0: FutureWarning: IPython widgets are experimental and may change in the future.

In [3]:

    

coin_flips = np.array([0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0])
n = len(coin_flips)
heads = len(filter(lambda x: x == 0, coin_flips))


    

In [6]:

    

with pm.Model() as model:
    prior = pm.Beta('prior', alpha=1, beta=1)
    likelihood = pm.Binomial('flips', p=prior, n=n, observed=heads)
    step = pm.NUTS()
    trace = pm.sample(50000, step)


    

    




 [-----------------100%-----------------] 50000 of 50000 complete in 15.0 sec

In [5]:

    

pm.traceplot(trace[1000:])


    

    
Out[5]:












    

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