/usr/lib/python2.7/dist-packages/pymc/examples/disaster_model_null.py is in python-pymc 2.2+ds-1.1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | """
A model for the disasters data with no changepoint:
global_rate ~ Exp(3.)
disasters[t] ~ Po(global_rate)
"""
from pymc import *
from numpy import array
__all__ = ['global_rate', 'disasters', 'disasters_array']
disasters_array = array([ 4, 5, 4, 0, 1, 4, 3, 4, 0, 6, 3, 3, 4, 0, 2, 6,
3, 3, 5, 4, 5, 3, 1, 4, 4, 1, 5, 5, 3, 4, 2, 5,
2, 2, 3, 4, 2, 1, 3, 2, 2, 1, 1, 1, 1, 3, 0, 0,
1, 0, 1, 1, 0, 0, 3, 1, 0, 3, 2, 2, 0, 1, 1, 1,
0, 1, 0, 1, 0, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 2,
3, 3, 1, 1, 2, 1, 1, 1, 1, 2, 4, 2, 0, 0, 1, 4,
0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1])
# Define the data and stochastics
global_rate = Exponential('global_rate',beta=1./3)
@stochastic(observed=True, dtype=int)
def disasters(value = disasters_array, rate = global_rate):
"""Annual occurences of coal mining disasters."""
return poisson_like(value, rate)
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