Fitting Lognormal Data

[scidam]

Lets consider for exmaple the following piece of code:

import numpy as np 
from scipy import stats
x = 2 * np.random.randn(10000) + 7.0 # normally  distributed values
y = np.exp(x) # these values have lognormal distribution
stats.lognorm.fit(y, floc=0)
(1.9780155814544627, 0, 1070.4207866985835) #so, sigma = 1.9780155814544627 approx 2.0
np.log(1070.4207866985835) #yields 6.9758071087468636 approx 7.0

So, everything works fine: sigma and mu are estimated correctly...
What about sample sizes in your case? The example above shows that we have to
use very large samples to get high accuracy estimations.