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
- residarray_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.
- storebool,
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.
- lm
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.