statsmodels.stats.diagnostic.acorr_lm¶

statsmodels.stats.diagnostic.acorr_lm(resid, nlags=None, store=False, *, period=None, ddof=0, cov_type='nonrobust', cov_kwargs=None)[source]¶

Lagrange Multiplier tests for autocorrelation.

This is a generic Lagrange Multiplier test for autocorrelation. Returns Engle’s ARCH test if resid is the squared residual array. Breusch-Godfrey is a variation on this test with additional exogenous variables.

Parameters:¶

resid : array_like¶: Time series to test.
nlags : int, default None¶: Highest lag to use.
store : bool, default False¶: If true then the intermediate results are also returned.
period : int, default none¶: The period of a Seasonal time series. Used to compute the max lag for seasonal data which uses min(2*period, nobs // 5) if set. If None, then the default rule is used to set the number of lags. When set, must be >= 2.
ddof : int, default 0¶: The number of degrees of freedom consumed by the model used to produce resid. The default value is 0.
cov_type : str, default "nonrobust"¶: Covariance type. The default is “nonrobust` which uses the classic OLS covariance estimator. Specify one of “HC0”, “HC1”, “HC2”, “HC3” to use White’s covariance estimator. All covariance types supported by OLS.fit are accepted.
cov_kwargs : dict, default None¶: Dictionary of covariance options passed to OLS.fit. See OLS.fit for more details.

Returns:¶

lm (float) – Lagrange multiplier test statistic.
lmpval (float) – The p-value for Lagrange multiplier test.
fval (float) – The f statistic of the F test, alternative version of the same test based on F test for the parameter restriction.
fpval (float) – The pvalue of the F test.
res_store (ResultsStore, optional) – Intermediate results. Only returned if store=True.