Python binom_tost_reject_intervalの例

コード例 #1

ファイル: test_proportion.py プロジェクト: gregcole/statsmodels

def test_power_binom_tost():
    # comparison numbers from PASS manual
    p_alt = 0.6 + np.linspace(0, 0.09, 10)
    power = smprop.power_binom_tost(0.5, 0.7, 500, p_alt=p_alt, alpha=0.05)
    res_power = np.array([0.9965,  0.9940,  0.9815,  0.9482,  0.8783,  0.7583,
                          0.5914,  0.4041,  0.2352,  0.1139])
    assert_almost_equal(power, res_power, decimal=4)

    rej_int = smprop.binom_tost_reject_interval(0.5, 0.7, 500)
    res_rej_int = (269, 332)
    assert_equal(rej_int, res_rej_int)

    # TODO: actual alpha=0.0489  for all p_alt above

    # another case
    nobs = np.arange(20, 210, 20)
    power = smprop.power_binom_tost(0.4, 0.6, nobs, p_alt=0.5, alpha=0.05)
    res_power = np.array([ 0.,  0.,  0.,  0.0889,  0.2356,  0.3517,  0.4457,
                           0.6154,  0.6674,  0.7708])
    # TODO: I currently don't impose power>=0, i.e np.maximum(power, 0)
    assert_almost_equal(np.maximum(power, 0), res_power, decimal=4)

コード例 #2

ファイル: test_proportion.py プロジェクト: GonzaloUlla/Bankruptcy-Prediction-using-Machine-Learning-Algorithms-in-Python

def test_power_binom_tost():
    # comparison numbers from PASS manual
    p_alt = 0.6 + np.linspace(0, 0.09, 10)
    power = smprop.power_binom_tost(0.5, 0.7, 500, p_alt=p_alt, alpha=0.05)
    res_power = np.array([0.9965,  0.9940,  0.9815,  0.9482,  0.8783,  0.7583,
                          0.5914,  0.4041,  0.2352,  0.1139])
    assert_almost_equal(power, res_power, decimal=4)

    rej_int = smprop.binom_tost_reject_interval(0.5, 0.7, 500)
    res_rej_int = (269, 332)
    assert_equal(rej_int, res_rej_int)

    # TODO: actual alpha=0.0489  for all p_alt above

    # another case
    nobs = np.arange(20, 210, 20)
    power = smprop.power_binom_tost(0.4, 0.6, nobs, p_alt=0.5, alpha=0.05)
    res_power = np.array([ 0.,  0.,  0.,  0.0889,  0.2356,  0.3517,  0.4457,
                           0.6154,  0.6674,  0.7708])
    # TODO: I currently don't impose power>=0, i.e np.maximum(power, 0)
    assert_almost_equal(np.maximum(power, 0), res_power, decimal=4)