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unitroot_test

Get Unit Root Test.

This function applies two renowned tests to assess whether your data series is stationary or if it contains a unit root, indicating it may be influenced by time-based trends or seasonality. The Augmented Dickey-Fuller (ADF) test helps identify the presence of a unit root, suggesting that the series could be non-stationary and potentially unpredictable over time. On the other hand, the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test checks for the stationarity of the series, where failing to reject the null hypothesis indicates a stable, stationary series. Together, these tests provide a comprehensive view of your data's time series properties, essential for accurate modeling and forecasting.

Parameters​

data: list[openbb_core.provider.abstract.data.Data]

Time series data.

• Optional: False

target: str

Target column name.

• Optional: False

fuller_reg: Literal['c', 'ct', 'ctt', 'nc']

Regression type for ADF test.

• Default: c

• Optional: True

kpss_reg: Literal['c', 'ct']

Regression type for KPSS test.

• Default: c

• Optional: True

Returns​

results: list[UnitRootModel]

Serializable results.

provider: None

Provider name.

warnings: Optional[list[Warning_]]

list of warnings.

chart: Optional[Chart]

Chart object.

extra: dict[str, Any]

Extra info.

Data​

adf: ADFTestModel

kpss: KPSSTestModel

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