statsmodels.tsa.stattools.ADFullerResult#

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

Result of adfuller.

Parameters:

adffloat: The test statistic.
pvaluefloat: MacKinnon’s approximate p-value based on MacKinnon (1994, 2010).
usedlagint: 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.

Methods

`count`(value, /)	Return number of occurrences of value.
`index`(value[, start, stop])	Return first index of value.

Methods

`count`(value, /)	Return number of occurrences of value.
`index`(value[, start, stop])	Return first index of value.

Properties