In [23]:
class ECDF(object):
def __init__(self, observations):
self.observations = observations
def __call__(self, x):
counter = 0.0
for i in range(len(self.observations)):
if self.observations[i] <= x:
counter += 1
return counter / len(self.observations)
In [24]:
from random import uniform
samples = [uniform(0, 1) for i in range(10)]
F = ECDF(samples)
print(F(0.5)) # Evaluate ecdf at x = 0.5
In [19]:
ecdf = ECDF(3)
In [20]:
ecdf.renshu(5)
In [17]:
ecdf.renshu2()
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