class_docstr: Test for stationarity via the Kwiatkowski-Phillips-Schmidt-Shin Unit Root Test.
  
  Direct interface to ``KPSS`` test from the ``arch`` package.
  Does not assume ARCH process, naming is due to the use of the ``arch`` package.
  
  Uses ``arch.unitroot.KPSS`` as a test for trend-stationarity,
  and derives a boolean statement whether a series is (trend-)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 Newey-West estimator of the long-run
      covariance.  If omitted or None, the number of lags is calculated
      with the data-dependent method of Hobijn et al. (1998). See also
      Andrews (1991), Newey & West (1994), and Schwert (1989).
      Set ``lags=-1`` to use the old method that only depends on the sample
      size, ``12 * (nobs/100) ** (1/4)``.
  trend : {"c", "ct"}, optional
      The trend component to include in the ADF test
          "c" - Include a constant (Default)
          "ct" - Include a constant and linear time trend
  
  Attributes
  ----------
  stationary_ : bool
      whether the series in ``fit`` is stationary according to the test
      more precisely, whether the null of the KPSS test is accepted at ``p_threshold``
  test_statistic_ : float
      The KPSS test statistic, of running ``KPSS`` on ``y`` in ``fit``
  pvalue_ : float : float
      p-value obtained when running ``KPSS`` 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 StationarityKPSSArch
  >>>
  >>> X = load_airline()  # doctest: +SKIP
  >>> sty_est = StationarityKPSSArch()  # doctest: +SKIP
  >>> sty_est.fit(X)  # doctest: +SKIP
  StationarityKPSSArch(...)
  >>> sty_est.get_fitted_params()["stationary"]  # doctest: +SKIP
  True
code: def __init__(
      self,
      lags=None,
      trend="c",
      p_threshold=0.05,
  ):
      self.lags = lags
      self.trend = trend
      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 StationarityKPSSArch object from inherited base classes: BaseParamFitter with example: obj = StationarityKPSSArch(lags, trend, p_threshold)