class_docstr: Test for unit root order 1 via the Phillips-Perron Unit Root Test.
  
  Direct interface to ``PhillipsPerron`` test from the ``arch`` package.
  
  Uses ``arch.unitroot.PhillipsPerron`` 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 Newey-West estimator of the long-run
      covariance. If omitted or None, the lag length is set automatically to
      ``12 * (nobs/100) ** (1/4)``
  trend : {"n", "c", "ct"}, optional
      The trend component to include in the test
  
      - "n" - No trend components
      - "c" - Include a constant (Default)
      - "ct" - Include a constant and linear time trend
  
  test_type : {"tau", "rho"}
      The test to use when computing the test statistic. "tau" is based on
      the t-stat and "rho" uses a test based on nobs times the re-centered
      regression coefficient
  
  Attributes
  ----------
  stationary_ : bool
      whether the series in ``fit`` is integrated of order 1
      more precisely, whether the null of the Phillips-Perron test is rejected at
      ``p_threshold``
  test_statistic_ : float
      The PP test statistic, of running ``PhillipsPerron`` on ``y`` in ``fit``
  pvalue_ : float : float
      p-value obtained when running ``PhillipsPerron`` 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 StationarityPhillipsPerron
  >>>
  >>> X = load_airline()  # doctest: +SKIP
  >>> sty_est = StationarityPhillipsPerron()  # doctest: +SKIP
  >>> sty_est.fit(X)  # doctest: +SKIP
  StationarityPhillipsPerron(...)
  >>> sty_est.get_fitted_params()["stationary"]  # doctest: +SKIP
  False
code: def __init__(
      self,
      lags=None,
      trend="c",
      test_type="tau",
      p_threshold=0.05,
  ):
      self.lags = lags
      self.trend = trend
      self.test_type = test_type
      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 StationarityPhillipsPerron object from inherited base classes: BaseParamFitter with example: obj = StationarityPhillipsPerron(lags, trend, test_type, p_threshold)