[SciPy-User] MLE with stats.lognorm

[Christian K.]

Hi,

I wonder whether I am doing something wrong or if the following is to be 
expected (using sciyp 0.9):

In [38]: from scipy import stats

In [39]: dist = stats.lognorm(0.25,scale=200.0)

In [40]: samples = dist.rvs(size=100)

In [41]: print stats.lognorm.fit(samples)
C:\Python26\lib\site-packages\scipy\optimize\optimize.py:280: RuntimeWarning: 
invalid value encountered in subtract
  and max(abs(fsim[0]-fsim[1:])) <= ftol):
(1.0, 158.90310231282845, 21.013288720647015)

In [42]: print stats.lognorm.fit(samples, floc=0)
[2.2059200167655884, 0, 21.013288720647015]

Even when fixing loc=0.0, the results from the MLE for s and scale are very 
different from the input parameters. Is lognorm 

Any hints are highly appreciated.

Best regards, Christian