This post shows how to fit a probability distribution using the Scipy Library.
Probability distributions fitting with Python
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Probability distributions fitting with Python
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Re: Probability distributions fitting with Python
#2Summary: 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
Re: Probability distributions fitting with Python
#3I 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.
Re: Probability distributions fitting with Python
#4Thanks 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.
Re: Probability distributions fitting with Python
#5This is regularly done in R using the MASS library.