NormalFit

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fonnesbeck edited this page Mar 30, 2013 · 3 revisions

Put the following into simple.py:

import pymc
import numpy

numpy.random.seed(15)

true_mu = 1.5
true_tau = 50.0
N_samples = 500

mu = pymc.Uniform('mu', lower=-100.0, upper=100.0)
tau = pymc.Gamma('tau', alpha=0.1, beta=0.001)

data = pymc.rnormal( true_mu, true_tau, size=(N_samples,) )

y = pymc.Normal('y',mu,tau,value=data,observed=True)

Then execute the following:

import pymc
import simple
from numpy import mean

model=pymc.MCMC(simple)
model.sample(iter=1000, burn=500, thin=2)

print 'mu',mean(model.trace('mu')[:])
print 'tau',mean(model.trace('tau')[:])