unit_root
Perform Augmented Dickey-Fuller (ADF) unit root test.
The ADF test is a popular method for testing the presence of a unit root in a time series. A unit root indicates that the series may be non-stationary, meaning its statistical properties such as mean, variance, and autocorrelation can change over time. The presence of a unit root suggests that the time series might be influenced by a random walk process, making it unpredictable and challenging for modeling and forecasting. The 'regression' parameter allows you to specify the model used in the test: 'c' for a constant term, 'ct' for a constant and trend term, and 'ctt' for a constant, linear, and quadratic trend. This flexibility helps tailor the test to the specific characteristics of your data, providing a more accurate assessment of its stationarity.
Parameters
- standard
data: list[openbb_core.provider.abstract.data.Data]
Input dataset.
• Optional: False
column: str
Data columns to check unit root
• Optional: False
regression: Literal['c', 'ct', 'ctt']
Regression type to use in the test. Either 'c' for constant only, 'ct' for constant and trend, or 'ctt' for
• Default: c
• Optional: True
Returns
results: list[Data]
Serializable results.
provider: None
Provider name.
warnings: Optional[list[Warning_]]
list of warnings.
chart: Optional[Chart]
Chart object.
extra: dict[str, Any]
Extra info.