def setup_class(cls):
data = sm.datasets.sunspots.load(as_pandas=False)
cls.res1 = AutoReg(data.endog, lags=9, trend='n',
old_names=False).fit()
cls.res2 = results_ar.ARResultsOLS(constant=False)
def setup_class(cls):
data = sm.datasets.sunspots.load(as_pandas=True)
data.endog.index = list(range(len(data.endog)))
cls.res1 = AutoReg(data.endog, lags=9, old_names=False).fit()
cls.res2 = results_ar.ARResultsOLS(constant=True)
def setup_class(cls):
data = sm.datasets.sunspots.load(as_pandas=False)
with pytest.warns(FutureWarning):
cls.res1 = AR(data.endog).fit(maxlag=9, method='cmle', trend='nc')
cls.res2 = results_ar.ARResultsOLS(constant=False)
def setup_class(cls):
data = sunspots.load()
cls.res1 = AutoReg(np.asarray(data.endog), lags=9, trend="n").fit()
cls.res2 = results_ar.ARResultsOLS(constant=False)
def setup_class(cls):
data = sunspots.load()
data.endog.index = list(range(len(data.endog)))
cls.res1 = AutoReg(data.endog, lags=9).fit()
cls.res2 = results_ar.ARResultsOLS(constant=True)
def setup_class(cls):
data = sm.datasets.sunspots.load(as_pandas=True)
cls.res1 = AutoReg(data.endog, lags=9).fit()
cls.res2 = results_ar.ARResultsOLS(constant=True)
