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Last active October 30, 2015 22:11
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For a forthcoming blog post.
from pylab import *
from scipy.stats import uniform
gamma = 0.01/12.0
t = arange(0,360)
def compute_payout(payout):
return (payout * exp( - gamma * t)).sum()
def generate_payout():
payout = ones(shape=(1,360)) * 100
for k in range(360):
if uniform().rvs() < 0.01/12.0:
payout[:,k:] = 0.0
return payout
N = 100000
values = zeros(shape=(N,), dtype=float)
for i in range(N):
values[i] = compute_payout(generate_payout())
hist(values, bins=50, normed=True)
xlabel("Total payout")
ylabel("Approximate probability density")
show()
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