statsmodels.tsa.stattools.ADFullerResult#

class statsmodels.tsa.stattools.ADFullerResult(statistic, pvalue, lags, nobs, critical_values, icbest, resstore)[source]#

Result of adfuller.

Parameters:

statisticfloat: The test statistic.
pvaluefloat: MacKinnon’s approximate p-value based on MacKinnon (1994, 2010).
lagsint: The number of lags used.
nobsint: The number of observations used for the ADF regression and calculation of the critical values.
critical_valuesdict[str, float]: Critical values for the test statistic at the 1 %, 5 %, and 10 % levels. Based on MacKinnon (2010).
icbestfloat or None: The maximized information criterion if autolag is not None, otherwise None.
resstoreResultsStore or None: A dummy class with results attached as attributes, if store was True, otherwise None.

Attributes:

Notes

Unpacks as statistic, pvalue = result. Other values are only accessible using attributes.

Methods

Properties