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how to calculate overlaping coefficient between two probablity functions
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how to calculate overlaping coefficient between two probablity functions
#1
I have two probability density functions generated as follows:

location = 0.97
scale = 1.0
x = np.linspace(-5,5,100)

plt.subplots(figsize=(12,4))

pdf1 = skew_norm_pdf(x,location,scale,SKEW_PARAMS[0])

pdf2 = skew_norm_pdf(x, location, scale, SKEW_PARAMS[1]

How can I calculate the overlapping coefficient between the two generated probability density funtions?
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#2
In theory you can do it by finding the places where the pdfs intersect, then use the cdf. For example if pdf1(x) < pdf2(x) for all x in an interval (a, b) then you can add cdf1(b) - cdf1(a) to the overlapping coefficient.
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#3
Hi can you please explain this further, will be nice if you could add some simple scrip to do this? Moreover how do I know pdf1(x) < pdf2(x)?
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#4
How can I find the overlap between the following distributions?

from import scipy.stats

np.random.seed(seed=233423)

R1 = scipy.stats.skewnorm(2, 0, 2).rvs(1000)
R2 = scipy.stats.skewnorm(3, 1, 2).rvs(1000)
how to find the overlap between R1 and R2 in python?

These are two randomly generated distributions
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