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Param Estimator

StationarityADFArch

API-ReferenzQuellcode

Test for stationarity via the Augmented Dickey-Fuller Unit Root Test (ADF).

Direct interface to DFGLS test from the arch package. Does not assume ARCH process, naming is due to the use of the arch package.

Uses arch.unitroot.ADF 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 StationarityADFArch

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

Parameter(5)

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{“n”, “c”, “ct”, “ctt”}, 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

  • “ctt” - Include a constant and linear and quadratic time trends

max_lagsint, 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

low_memorybool
Flag indicating whether to use a low memory implementation of the lag selection algorithm. The low memory algorithm is slower than the standard algorithm but will use 2-4% of the memory required for the standard algorithm. This options allows automatic lag selection to be used in very long time series. If None, use automatic selection of algorithm.

Beispiele

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