[SciPy-Dev] weird results in frozen distribution fit

[josef.pktd@gmai...]

Given a report on the scipy-user mailing list
http://projects.scipy.org/scipy/ticket/1536 I started for the first
time to look at some examples with the frozen fit introduced in scipy
0.9.  I just picked randomly some distributions that came to mind,
except for the reported lognorm.

some cases look ok, maybe. Some cases look "weird"

Josef

lognorm true
0.25 0.0 20.0
estimated, floc=0, loc=0
[ 2.1221  0.      2.4403] [  0.2303  -1.8759  21.9986]
[ 2.1454  0.      2.3763] [  0.2446   0.0305  19.9945]
[ 2.1274  0.      2.414 ] [  0.2469   0.0296  19.9415]
[ 2.1362  0.      2.3897] [  0.2525   0.4579  19.4758]
[ 2.1334  0.      2.4104] [  0.2484   0.0298  20.0291]
[ 2.1033  0.      2.475 ] [  2.5335e-01   1.0858e-02   1.9959e+01]
[ 2.1266  0.      2.414 ] [  0.2662   1.3626  18.5458]
[ 2.1316  0.      2.4176] [  0.2491   0.0299  20.0509]
[ 2.0897  0.      2.5211] [  0.276    1.4881  18.5202]
[ 2.1382  0.      2.3738] [  0.2465   0.0301  19.8241]
gamma true
2 20 10.0
estimated, floc=0, loc=0
[  2.0945  20.       9.6182] [  1.9864  20.0832  10.2119] [  2.0317
20.      10.    ]
[  2.0084  20.      10.101 ] [  1.9364  20.1738  10.41  ] [  2.0241
20.      10.    ]
[  2.1359  20.       9.1555] [  2.0353  19.8413   9.8974] [  1.9937
20.      10.    ]
[  2.2296  20.       8.6785] [  2.152   19.8834   9.1795] [  1.9948
20.      10.    ]
[  1.8822  20.      10.8936] [  2.0389  19.9836   9.8365] [  2.0104
20.      10.    ]
[  1.8304  20.      11.3802] [  2.0341  20.169    9.7599] [  2.0214
20.      10.    ]
[  1.972   20.       9.7958] [  1.9107  20.0777  10.1223] [  1.9409
20.      10.    ]
[  1.6211  20.      13.3028] [  1.9636  20.1903  10.1156] [  2.0103
20.      10.    ]
[  2.0413  20.       9.8165] [  2.0238  19.9456   9.9794] [  2.0121
20.      10.    ]
[  2.0087  20.      10.1362] [  2.0128  20.1212   9.9924] [  2.0299
20.      10.    ]
normal true
0.0 2.0
estimated, floc=0, loc=0, fscale=2
[ 0.      2.0024] [-0.0417  2.0024] [-0.0417  2.    ]
[ 0.      2.0003] [-0.0879  2.0003] [-0.0879  2.    ]
[ 0.      1.9466] [-0.0133  1.9466] [-0.0133  2.    ]
[ 0.      1.9726] [-0.036   1.9726] [-0.0359  2.    ]
[ 0.      2.0007] [-0.0194  2.0007] [-0.0195  2.    ]
[ 0.      1.9565] [ 0.0338  1.9565] [ 0.0337  2.    ]
[ 0.      1.9674] [ 0.0288  1.9674] [ 0.0289  2.    ]
[ 0.      1.9962] [ 0.0051  1.9962] [ 0.0051  2.    ]
[ 0.      1.8901] [ 0.0179  1.8901] [ 0.0179  2.    ]
[ 0.      2.0017] [ 0.0307  2.0017] [ 0.0307  2.    ]
chi2 true
10 0.0 2.0
estimated, floc=0, loc=0
[ 3.8459  0.      6.1457] [ 10.9616  -0.6938   1.8646]
[ 3.8314  0.      6.3129] [ 10.4894  -0.295    1.9516]
[ 3.7449  0.      6.4353] [ 9.7304 -0.0364  2.0654]
[ 3.8094  0.      6.2268] [ 10.4314  -0.3388   1.9283]
[ 3.69    0.      6.5633] [ 8.4951  1.1035  2.2316]
[ 3.6475  0.      6.6415] [ 8.3315  0.8241  2.3152]
[ 3.7288  0.      6.4983] [ 9.4114  0.2128  2.1185]
[ 3.8005  0.      6.2852] [ 10.0038  -0.0154   1.9917]
[ 3.7384  0.      6.4327] [ 8.4504  1.1931  2.224 ]
[ 3.9063  0.      6.0929] [ 10.3413   0.2105   1.902 ]
>>>
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