Param Estimator

StationarityPhillipsPerron

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.

Schnellstart

python

from sktime.param_est.stationarity import StationarityPhillipsPerron

estimator = StationarityPhillipsPerron(lags=None, trend='c', test_type='tau', p_threshold=0.05)

Parameter(3)

lagsint, 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

Beispiele

>>> from sktime.datasets import load_airline
>>> from sktime.param_est.stationarity import StationarityPhillipsPerron
>>> 
>>> X = load_airline ()
>>> sty_est = StationarityPhillipsPerron ()
>>> sty_est. fit (X) StationarityPhillipsPerron(
... )
>>> sty_est. get_fitted_params ()["stationary" ] False