def test_empirical_pvalues():
random = RandomState(1)
x0 = random.chisquare(1, 1000)
x1 = random.chisquare(1, 10000)
pv = empirical_pvalues(x0, x1)
assert_allclose(pv[:3], [0.5599, 1.0, 0.8389])
assert_allclose(pv[-3:], [0.249, 0.3278, 0.4848])
def test_chi2mixture():
dof = 2
mixture = 0.2
n = 100
random = RandomState(1)
x = random.chisquare(dof, n)
n0 = int((1 - mixture) * n)
idxs = random.choice(n, n0, replace=False)
x[idxs] = 0
chi2mix = Chi2Mixture(
scale_min=0.1,
scale_max=5.0,
dof_min=0.1,
dof_max=5.0,
qmax=0.1,
tol=4e-3,
lrt=x,
)
chi2mix.estimate_chi2mixture(x)
pv = chi2mix.sf([0.0, 0.2])
assert_allclose(pv, [0.19999999999999996, 0.1412935752078675])
assert_allclose(chi2mix.scale, 1.9808080808080812)
assert_allclose(chi2mix.dof, 0.891919191919192)
assert_allclose(chi2mix.mixture, 0.199999999999999960)
def test_multipletests():
random = RandomState(5)
pv = multipletests(random.chisquare(1, 10))[1]
assert_allclose(
pv,
[
0.56399935,
0.55249248,
0.96090415,
0.99606969,
0.74247325,
0.12299317,
1.0,
0.91970786,
0.99606969,
0.99595594,
],
)
