

Probability distributions fitting with Python - Manuelito
http://glowingpython.blogspot.it/2012/07/distribution-fitting-with-scipy.html
This post shows how to fit a probability distribution using the Scipy Library.
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imurray
Summary: The _fit_ method of the distributions in SciPy does maximum
likelihood fitting of parameters to data. This blog post gives a couple of
nice quick examples.

To see what else is available, one would go here:
<http://docs.scipy.org/doc/scipy/reference/stats.html>

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sirclueless
I just want to point out that "we can observe that they are really similar"
isn't likely to impress a statistician. It's possible to make a ballpark
estimate of how close they actually are because there is a graph with marked
axes, but the real derived parameters would be nice to know, and maybe even do
the legwork and calculate the expected error for your sample size.

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the_cat_kittles
Thanks for the heads up on a "Rayleigh distribution" (from
<http://en.wikipedia.org/wiki/Rayleigh_distribution>):

"One example where the Rayleigh distribution naturally arises is when wind
speed is analyzed into its orthogonal 2-dimensional vector components.
Assuming that the magnitude of each component is uncorrelated and normally
distributed with equal variance, then the overall wind speed (vector
magnitude) will be characterized by a Rayleigh distribution."

That is cool, I wonder if I will ever use it.

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probably
This is regularly done in R using the MASS library.

