本文整理汇总了Python中statsmodels.regression.linear_model.OLS.get_influence方法的典型用法代码示例。如果您正苦于以下问题：Python OLS.get_influence方法的具体用法？Python OLS.get_influence怎么用？Python OLS.get_influence使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类statsmodels.regression.linear_model.OLS的用法示例。
在下文中一共展示了OLS.get_influence方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_influence_dtype
# 需要导入模块: from statsmodels.regression.linear_model import OLS [as 别名]
# 或者: from statsmodels.regression.linear_model.OLS import get_influence [as 别名]
def test_influence_dtype():
# see #2148 bug when endog is integer
y = np.ones(20)
np.random.seed(123)
x = np.random.randn(20, 3)
res1 = OLS(y, x).fit()
res2 = OLS(y*1., x).fit()
cr1 = res1.get_influence().cov_ratio
cr2 = res2.get_influence().cov_ratio
assert_allclose(cr1, cr2, rtol=1e-14)
# regression test for values
cr3 = np.array(
[ 1.22239215, 1.31551021, 1.52671069, 1.05003921, 0.89099323,
1.57405066, 1.03230092, 0.95844196, 1.15531836, 1.21963623,
0.87699564, 1.16707748, 1.10481391, 0.98839447, 1.08999334,
1.35680102, 1.46227715, 1.45966708, 1.13659521, 1.22799038])
assert_almost_equal(cr1, cr3, decimal=8)示例2: test_outlier_influence_funcs
# 需要导入模块: from statsmodels.regression.linear_model import OLS [as 别名]
# 或者: from statsmodels.regression.linear_model.OLS import get_influence [as 别名]
def test_outlier_influence_funcs():
# smoke test
x = add_constant(np.random.randn(10, 2))
y = x.sum(1) + np.random.randn(10)
res = OLS(y, x).fit()
oi.summary_table(res, alpha=0.05)
res2 = OLS(y, x[:, 0]).fit()
oi.summary_table(res2, alpha=0.05)
infl = res2.get_influence()
infl.summary_table()示例3: test_outlier_influence_funcs
# 需要导入模块: from statsmodels.regression.linear_model import OLS [as 别名]
# 或者: from statsmodels.regression.linear_model.OLS import get_influence [as 别名]
def test_outlier_influence_funcs(reset_randomstate):
x = add_constant(np.random.randn(10, 2))
y = x.sum(1) + np.random.randn(10)
res = OLS(y, x).fit()
out_05 = oi.summary_table(res)
# GH3344 : Check alpha has an effect
out_01 = oi.summary_table(res, alpha=0.01)
assert_(np.all(out_01[1][:, 6] <= out_05[1][:, 6]))
assert_(np.all(out_01[1][:, 7] >= out_05[1][:, 7]))
res2 = OLS(y, x[:,0]).fit()
oi.summary_table(res2, alpha=0.05)
infl = res2.get_influence()
infl.summary_table()