Beispiel #1
0
def test_unequal_bs():
    def mean_diff(*args):
        return args[0].mean() - args[1].mean()

    rs = RandomState(0)
    x = rs.standard_normal(800)
    y = rs.standard_normal(200)

    bs = IndependentSamplesBootstrap(x, y, random_state=rs)
    variance = bs.var(mean_diff)
    assert variance > 0
    ci = bs.conf_int(mean_diff)
    assert ci[0] < ci[1]
    applied = bs.apply(mean_diff, 1000)
    assert len(applied) == 1000

    x = pd.Series(x)
    y = pd.Series(y)
    bs = IndependentSamplesBootstrap(x, y)
    variance = bs.var(mean_diff)
    assert variance > 0

    with pytest.raises(ValueError, match="BCa cannot be applied"):
        bs.conf_int(mean_diff, method="bca")
Beispiel #2
0
def test_unequal_bs():
    def mean_diff(*args):
        return args[0].mean() - args[1].mean()

    rs = RandomState(0)
    x = rs.randn(800)
    y = rs.randn(200)

    bs = IndependentSamplesBootstrap(x, y, random_state=rs)
    variance = bs.var(mean_diff)
    assert variance > 0
    ci = bs.conf_int(mean_diff)
    assert ci[0] < ci[1]
    applied = bs.apply(mean_diff, 1000)
    assert len(applied) == 1000

    x = pd.Series(x)
    y = pd.Series(y)
    bs = IndependentSamplesBootstrap(x, y)
    variance = bs.var(mean_diff)
    assert variance > 0
Beispiel #3
0
def test_unequal_bs():
    def mean_diff(*args):
        return args[0].mean() - args[1].mean()

    rs = RandomState(0)
    x = rs.randn(800)
    y = rs.randn(200)

    bs = IndependentSamplesBootstrap(x, y, random_state=rs)
    variance = bs.var(mean_diff)
    assert variance > 0
    ci = bs.conf_int(mean_diff)
    assert ci[0] < ci[1]
    applied = bs.apply(mean_diff, 1000)
    assert len(applied) == 1000

    x = pd.Series(x)
    y = pd.Series(y)
    bs = IndependentSamplesBootstrap(x, y)
    variance = bs.var(mean_diff)
    assert variance > 0
Beispiel #4
0
def test_unequal_bs_kwargs():
    def mean_diff(x, y):
        return x.mean() - y.mean()

    rs = RandomState(0)
    x = rs.standard_normal(800)
    y = rs.standard_normal(200)

    bs = IndependentSamplesBootstrap(x=x, y=y, random_state=rs)
    variance = bs.var(mean_diff)
    assert variance > 0
    ci = bs.conf_int(mean_diff)
    assert ci[0] < ci[1]
    applied = bs.apply(mean_diff, 1000)

    x = pd.Series(x)
    y = pd.Series(y)
    bs = IndependentSamplesBootstrap(x=x, y=y, random_state=rs)
    variance = bs.var(mean_diff)
    assert variance > 0

    assert len(applied) == 1000