class_docstr: Test for stationarity via the Dickey-Fuller GLS (DFGLS) Unit Root Test.
  
  Direct interface to ``DFGLS`` test from the ``arch`` package.
  
  Uses ``arch.unitroot.DFGLS`` as a test for unit roots,
  and derives a boolean statement whether a series is stationary.
  
  Also returns test results for the unit root test as fitted parameters.
  
  Parameters
  ----------
  lags : int, optional
      The number of lags to use in the ADF regression.  If omitted or None,
      ``method`` is used to automatically select the lag length with no more
      than ``max_lags`` are included.
  trend : {"c", "ct"}, optional
      The trend component to include in the test
  
      - "c" - Include a constant (Default)
      - "ct" - Include a constant and linear time trend
  
  max_lags : int, optional
      The maximum number of lags to use when selecting lag length. When using
      automatic lag length selection, the lag is selected using OLS
      detrending rather than GLS detrending ([2]_).
  method : {"AIC", "BIC", "t-stat"}, optional
      The method to use when selecting the lag length
  
      - "AIC" - Select the minimum of the Akaike IC
      - "BIC" - Select the minimum of the Schwarz/Bayesian IC
      - "t-stat" - Select the minimum of the Schwarz/Bayesian IC
  
  Attributes
  ----------
  stationary_ : bool
      whether the series in ``fit`` is stationary according to the test
      more precisely, whether the null of the Dickey-Fuller-GLS test is rejected at
      ``p_threshold``
  test_statistic_ : float
      The DFGLS test statistic, of running ``DFGLS`` on ``y`` in ``fit``
  pvalue_ : float : float
      p-value obtained when running ``DFGLS`` on ``y`` in ``fit``
  usedlag_ : int
      The number of lags used in the test.
  
  Examples
  --------
  >>> from sktime.datasets import load_airline
  >>> from sktime.param_est.stationarity import StationarityDFGLS
  >>>
  >>> X = load_airline()  # doctest: +SKIP
  >>> sty_est = StationarityDFGLS()  # doctest: +SKIP
  >>> sty_est.fit(X)  # doctest: +SKIP
  StationarityDFGLS(...)
  >>> sty_est.get_fitted_params()["stationary"]  # doctest: +SKIP
  False
code: def __init__(
      self,
      lags=None,
      trend="c",
      max_lags=None,
      method="aic",
      p_threshold=0.05,
  ):
      self.lags = lags
      self.trend = trend
      self.max_lags = max_lags
      self.method = method
      self.p_threshold = p_threshold
      super().__init__()
  
imports: from sktime.param_est.base import BaseParamFitter
label_desc: Use image node_id 1 to create a new StationarityDFGLS object from inherited base classes: BaseParamFitter with example: obj = StationarityDFGLS(lags, trend, max_lags, method, p_threshold)