Fix test for dev version of statsmodels (mlflow#4570)

* Fix test for dev version of statsmodels

Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>

* apply asarray

Signed-off-by: harupy <hkawamura0130@gmail.com>

* remove unnecessary blank line

Signed-off-by: harupy <hkawamura0130@gmail.com>

* fix comment

Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>

* remove if-else

Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>

* remove unused import

Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>

tests/statsmodels/model_fixtures.py

@@ -7,6 +7,7 @@
 from statsmodels.tsa.arima.model import ARIMA
 from scipy.linalg import toeplitz
 
+
 ModelWithResults = namedtuple("ModelWithResults", ["model", "alg", "inference_dataframe"])
 
 
@@ -51,10 +52,18 @@ def failing_logit_model():
     return ModelWithResults(model=model, alg=log_reg, inference_dataframe=X)
 
 
+def get_dataset(name):
+    dataset_module = getattr(sm.datasets, name)
+    data = dataset_module.load()
+    data.exog = np.asarray(data.exog)
+    data.endog = np.asarray(data.endog)
+    return data
+
+
 @pytest.fixture(scope="session")
 def gls_model():
     # Generalized Least Squares (GLS)
-    data = sm.datasets.longley.load(as_pandas=False)
+    data = get_dataset("longley")
     data.exog = sm.add_constant(data.exog)
     ols_resid = sm.OLS(data.endog, data.exog).fit().resid
     res_fit = sm.OLS(ols_resid[1:], ols_resid[:-1]).fit()
@@ -114,7 +123,7 @@ def rolling_ols_model():
     # Rolling Ordinary Least Squares (Rolling OLS)
     from statsmodels.regression.rolling import RollingOLS
 
-    data = sm.datasets.longley.load(as_pandas=False)
+    data = get_dataset("longley")
     exog = sm.add_constant(data.exog, prepend=False)
     rolling_ols = RollingOLS(data.endog, exog)
     model = rolling_ols.fit(reset=50)
@@ -127,7 +136,7 @@ def rolling_wls_model():
     # Rolling Weighted Least Squares (Rolling WLS)
     from statsmodels.regression.rolling import RollingWLS
 
-    data = sm.datasets.longley.load(as_pandas=False)
+    data = get_dataset("longley")
     exog = sm.add_constant(data.exog, prepend=False)
     rolling_wls = RollingWLS(data.endog, exog)
     model = rolling_wls.fit(reset=50)
@@ -187,7 +196,7 @@ def gee_model():
 @pytest.fixture(scope="session")
 def glm_model():
     # Generalized Linear Model (GLM)
-    data = sm.datasets.scotland.load(as_pandas=False)
+    data = get_dataset("scotland")
     data.exog = sm.add_constant(data.exog)
     glm = sm.GLM(data.endog, data.exog, family=sm.families.Gamma())
     model = glm.fit()