Comments (2)
It does look like there is a typo. Page 2 is pretty clear, but just to confirm:
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
rng = np.random.default_rng(23598345982)
m, n = 1000, 1000
N = 9999
x = rng.random((N, m))
y = rng.random((N, n))
res = stats.ks_2samp(x, y, axis=-1)
stat1 = np.sqrt((m*n)/(m + n) * res.statistic)
stat2 = np.sqrt((m*n)/(m + n)) * res.statistic
p = np.linspace(0, 10, 300)
pdf = stats.kstwobign.pdf(p)
bins = np.linspace(0, 10, 50)
plt.plot(p, pdf, label='pdf')
plt.hist(stat1, label='main', alpha=0.5, density=True)
plt.hist(stat2, label='suggested', alpha=0.5, density=True)
plt.legend()
@gianlucadetommaso Would you like to submit a PR? The file to edit is scipy/doc/source/tutorial/stats/continuous_kstwobign.rst. I can merge it.
from scipy.
Thanks for the quick reply! Sure, this should do it!
from scipy.
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from scipy.