def test_binom_tost():
# consistency check with two different implementation,
# proportion_confint is tested against R
# no reference case from other package available
ci = smprop.proportion_confint(10, 20, method='beta', alpha=0.1)
bt = smprop.binom_tost(10, 20, *ci)
assert_almost_equal(bt, [0.05] * 3, decimal=12)
ci = smprop.proportion_confint(5, 20, method='beta', alpha=0.1)
bt = smprop.binom_tost(5, 20, *ci)
assert_almost_equal(bt, [0.05] * 3, decimal=12)
# vectorized, TODO: observed proportion = 0 returns nan
ci = smprop.proportion_confint(np.arange(1, 20), 20, method='beta',
alpha=0.05)
bt = smprop.binom_tost(np.arange(1, 20), 20, *ci)
bt = np.asarray(bt)
assert_almost_equal(bt, 0.025 * np.ones(bt.shape), decimal=12)
def test_binom_tost():
# consistency check with two different implementation,
# proportion_confint is tested against R
# no reference case from other package available
ci = smprop.proportion_confint(10, 20, method='beta', alpha=0.1)
bt = smprop.binom_tost(10, 20, *ci)
assert_almost_equal(bt, [0.05] * 3, decimal=12)
ci = smprop.proportion_confint(5, 20, method='beta', alpha=0.1)
bt = smprop.binom_tost(5, 20, *ci)
assert_almost_equal(bt, [0.05] * 3, decimal=12)
# vectorized, TODO: observed proportion = 0 returns nan
ci = smprop.proportion_confint(np.arange(1, 20), 20, method='beta',
alpha=0.05)
bt = smprop.binom_tost(np.arange(1, 20), 20, *ci)
bt = np.asarray(bt)
assert_almost_equal(bt, 0.025 * np.ones(bt.shape), decimal=12)