class_docstr: Test for stationarity via the Zivot-Andrews Unit Root Test.
  
  Direct interface to ``ZivotAndrews`` test from the `arch` package.
  
  Uses ``arch.unitroot.ZivotAndrews`` 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", "t", "ct"}, optional
      The trend component to include in the test
  
      - "c" - Include a constant (Default)
      - "t" - Include a linear time trend
      - "ct" - Include a constant and linear time trend
  
  trim : float
      percentage of series at begin/end to exclude from break-period
      calculation in range [0, 0.333] (default=0.15)
  max_lags : int, optional
      The maximum number of lags to use when selecting lag length
  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` has a unit root
      (with structural break)
      more precisely, whether the null of the Zivot-Andrews test is rejected at
      ``p_threshold``
  test_statistic_ : float
      The ZA test statistic, of running ``ZivotAndrews`` on ``y`` in ``fit``
  pvalue_ : float : float
      p-value obtained when running ``ZivotAndrews`` 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 StationarityZivotAndrews
  >>>
  >>> X = load_airline()  # doctest: +SKIP
  >>> sty_est = StationarityZivotAndrews()  # doctest: +SKIP
  >>> sty_est.fit(X)  # doctest: +SKIP
  StationarityZivotAndrews(...)
  >>> sty_est.get_fitted_params()["stationary"]  # doctest: +SKIP
  False
docstr: Return testing parameter settings for the estimator.
  
  Parameters
  ----------
  parameter_set : str, default="default"
      Name of the set of test parameters to return, for use in tests. If no
      special parameters are defined for a value, will return `"default"` set.
      There are no reserved values for parameter estimators.
  
  Returns
  -------
  params : dict or list of dict, default = {}
      Parameters to create testing instances of the class
      Each dict are parameters to construct an "interesting" test instance, i.e.,
      `MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance.
      `create_test_instance` uses the first (or only) dictionary in `params`
docstr_tok: ["Return","testing","parameter","settings","for","the","estimator",".","Parameters","--","--","--","--","--","parameter_set",":","str",",","default=","''","default","''","Name","of","the","set","of","test","parameters","to","return",",","for","use","in","tests",".","If","no","special","parameters","are","defined","for","a","value",",","will","return","`","``","default","''","`","set",".","There","are","no","reserved","values","for","parameter","estimators",".","Returns","--","--","--","-","params",":","dict","or","list","of","dict",",","default","=","{","}","Parameters","to","create","testing","instances","of","the","class","Each","dict","are","parameters","to","construct","an","``","interesting","''","test","instance",",","i.e.",",","`","MyClass","(","*","*","params",")","`","or","`","MyClass","(","*","*","params","[","i","]",")","`","creates","a","valid","test","instance",".","`","create_test_instance","`","uses","the","first","(","or","only",")","dictionary","in","`","params","`"]
code: def get_test_params(cls, parameter_set="default"):
      """Return testing parameter settings for the estimator.
  
      Parameters
      ----------
      parameter_set : str, default="default"
          Name of the set of test parameters to return, for use in tests. If no
          special parameters are defined for a value, will return `"default"` set.
          There are no reserved values for parameter estimators.
  
      Returns
      -------
      params : dict or list of dict, default = {}
          Parameters to create testing instances of the class
          Each dict are parameters to construct an "interesting" test instance, i.e.,
          `MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance.
          `create_test_instance` uses the first (or only) dictionary in `params`
      """
      params1 = {}
      params2 = {
          "lags": 5,
          "trend": "ct",
          "trim": 0.1,
          "max_lags": 10,
          "method": "t-stat",
          "p_threshold": 0.1,
      }
  
      return [params1, params2]
  
imports: from sktime.param_est.base import BaseParamFitter
label_desc: Use image node_id 3 for calling the StationarityZivotAndrews obj's underlying member method code with example usage: obj.get_test_params(cls, parameter_set) and returns: list