def test_clustered_covariance_error(self):
with pytest.raises(ValueError):
ClusteredCovariance(self.y,
self.x,
self.params,
extra_df=0,
clusters=self.cluster5)
with pytest.raises(ValueError):
ClusteredCovariance(self.y,
self.x,
self.params,
extra_df=0,
clusters=self.cluster4[::2])
def test_clustered_covariance_smoke(self):
cov = ClusteredCovariance(self.y,
self.x,
self.params,
self.time_ids,
extra_df=0).cov
assert cov.shape == (self.k, self.k)
cov = ClusteredCovariance(self.y,
self.x,
self.params,
self.time_ids,
extra_df=0,
clusters=self.cluster1).cov
assert cov.shape == (self.k, self.k)
cov = ClusteredCovariance(self.y,
self.x,
self.params,
self.time_ids,
extra_df=0,
clusters=self.cluster2,
group_debias=True).cov
assert cov.shape == (self.k, self.k)
cov = ClusteredCovariance(self.y,
self.x,
self.params,
self.time_ids,
extra_df=0,
clusters=self.cluster3).cov
assert cov.shape == (self.k, self.k)
cov = ClusteredCovariance(self.y,
self.x,
self.params,
self.time_ids,
extra_df=0,
clusters=self.cluster3,
group_debias=True).cov
assert cov.shape == (self.k, self.k)
cov = ClusteredCovariance(self.y,
self.x,
self.params,
self.time_ids,
extra_df=0,
clusters=self.cluster4).cov
assert cov.shape == (self.k, self.k)
cov = ClusteredCovariance(self.y,
self.x,
self.params,
self.time_ids,
extra_df=0,
clusters=self.cluster4,
group_debias=True).cov
assert cov.shape == (self.k, self.k)
def test_clustered_covariance_error(panel_data) -> None:
with pytest.raises(ValueError):
ClusteredCovariance(
panel_data.y,
panel_data.x,
panel_data.params,
panel_data.entity_ids,
panel_data.time_ids,
extra_df=0,
clusters=panel_data.cluster5,
)
with pytest.raises(ValueError):
ClusteredCovariance(
panel_data.y,
panel_data.x,
panel_data.params,
panel_data.entity_ids,
panel_data.time_ids,
extra_df=0,
clusters=panel_data.cluster4[::2],
)
def test_clustered_covariance_error(self) -> None:
with pytest.raises(ValueError):
ClusteredCovariance(
self.y,
self.x,
self.params,
self.entity_ids,
self.time_ids,
extra_df=0,
clusters=self.cluster5,
)
with pytest.raises(ValueError):
ClusteredCovariance(
self.y,
self.x,
self.params,
self.entity_ids,
self.time_ids,
extra_df=0,
clusters=self.cluster4[::2],
)
def test_clustered_covariance_smoke(panel_data) -> None:
cov = ClusteredCovariance(
panel_data.y,
panel_data.x,
panel_data.params,
panel_data.entity_ids,
panel_data.time_ids,
extra_df=0,
).cov
assert cov.shape == (panel_data.k, panel_data.k)
cov = ClusteredCovariance(
panel_data.y,
panel_data.x,
panel_data.params,
panel_data.entity_ids,
panel_data.time_ids,
extra_df=0,
clusters=panel_data.cluster1,
).cov
assert cov.shape == (panel_data.k, panel_data.k)
cov = ClusteredCovariance(
panel_data.y,
panel_data.x,
panel_data.params,
panel_data.entity_ids,
panel_data.time_ids,
extra_df=0,
clusters=panel_data.cluster2,
group_debias=True,
).cov
assert cov.shape == (panel_data.k, panel_data.k)
cov = ClusteredCovariance(
panel_data.y,
panel_data.x,
panel_data.params,
panel_data.entity_ids,
panel_data.time_ids,
extra_df=0,
clusters=panel_data.cluster3,
).cov
assert cov.shape == (panel_data.k, panel_data.k)
cov = ClusteredCovariance(
panel_data.y,
panel_data.x,
panel_data.params,
panel_data.entity_ids,
panel_data.time_ids,
extra_df=0,
clusters=panel_data.cluster3,
group_debias=True,
).cov
assert cov.shape == (panel_data.k, panel_data.k)
cov = ClusteredCovariance(
panel_data.y,
panel_data.x,
panel_data.params,
panel_data.entity_ids,
panel_data.time_ids,
extra_df=0,
clusters=panel_data.cluster4,
).cov
assert cov.shape == (panel_data.k, panel_data.k)
cov = ClusteredCovariance(
panel_data.y,
panel_data.x,
panel_data.params,
panel_data.entity_ids,
panel_data.time_ids,
extra_df=0,
clusters=panel_data.cluster4,
group_debias=True,
).cov
assert cov.shape == (panel_data.k, panel_data.k)