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Param Estimator

StationarityDFGLS

API referenceSource

Test for stationarity via the Dickey-Fuller GLS (DFGLS) Unit Root Test.

Quickstart

python
from sktime.param_est.stationarity import StationarityDFGLS

estimator = StationarityDFGLS(lags=None, trend='c', max_lags=None, method='aic', p_threshold=0.05)

Parameters(4)

lagsint, 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_lagsint, 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

Examples

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