def test_smoke(data, trend, lags, leads, common, max_lag, method):
y, x = data
if common:
leads = lags
mod = DynamicOLS(y, x, trend, lags, leads, common, max_lag, max_lag,
method)
mod.fit()
def test_smoke_fit(data, cov_type, kernel, bandwidth, force_int, df_adjust):
y, x = data
mod = DynamicOLS(y, x, "ct", 3, 5, False)
res = mod.fit(cov_type, kernel, bandwidth, force_int, df_adjust)
assert isinstance(res.leads, int)
assert isinstance(res.lags, int)
assert isinstance(res.bandwidth, (int, float))
assert isinstance(res.params, pd.Series)
assert isinstance(res.cov_type, str)
assert isinstance(res.resid, pd.Series)
assert isinstance(res.cov, pd.DataFrame)
assert isinstance(res.kernel, str)
assert isinstance(res.summary().as_text(), str)
assert isinstance(res.summary(True).as_text(), str)