class_docstr: Conduct an ADF test for stationarity.
  
  In statistics and econometrics, an augmented Dickey–Fuller test (ADF)
  tests the null hypothesis of a unit root is present in a time series
  sample. The alternative hypothesis is different depending on which version
  of the test is used, but is usually stationarity or trend-stationarity. It
  is an augmented version of the Dickey–Fuller test for a larger and more
  complicated set of time series models.
  
  Parameters
  ----------
  alpha : float, optional (default=0.05)
      Level of the test
  
  k : int, optional (default=None)
      The drift parameter. If ``k`` is None, it will be set to:
      ``np.trunc(np.power(x.shape[0] - 1, 1 / 3.0))``
  
  Notes
  -----
  This test is generally used indirectly via the
  :func:`pmdarima.arima.ndiffs` function, which computes the
  differencing term, ``d``.
  
  ADF test does not perform as close to the R code as do the KPSS and PP
  tests. This is due to the fact that is has to use statsmodels OLS
  regression for std err estimates rather than the more robust sklearn
  LinearRegression.
  
  References
  ----------
  .. [1] https://wikipedia.org/wiki/Augmented_Dickey–Fuller_test
  .. [2] R's tseries ADF source code: https://bit.ly/2EnvM5V
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code: def _ols_std_error(res):
      stderrs = res.bse  # this was a pain in the ARSE to locate
      return res.params[1] / stderrs[1]
  
imports: from sklearn.base import BaseEstimator
  from sklearn.linear_model import LinearRegression
  from statsmodels import api
  from abc import ABCMeta, abstractmethod
  import numpy
  from ..compat.numpy import DTYPE
  from ..decorators import deprecated
  from ..utils.array import c, diff, check_endog
  from .approx import approx
  from ._arima import C_tseries_pp_sum
label_desc: Use image node_id 3 for calling the ADFTest obj's underlying member method code with example usage: obj._ols_std_error(res) and returns: unknown