statsmodels.stats.diagnostic.acorr_lm¶
-
statsmodels.stats.diagnostic.
acorr_lm
(resid, nlags=None, autolag='AIC', 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. The behavior of this parameter will change after 0.12.
autolag : {str, None}, default “AIC”
If None, then a fixed number of lags given by maxlag is used. This parameter is deprecated and will be removed after 0.12. Searching for model specification cannot control test size.
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.
See also
het_arch
- Conditional heteroskedasticity testing.
acorr_breusch_godfrey
- Breusch-Godfrey test for serial correlation.
acorr_ljung_box
- Ljung-Box test for serial correlation.
Notes
The test statistic is computed as (nobs - ddof) * r2 where r2 is the R-squared from a regression on the residual on nlags lags of the residual.