stats.diagnostic.acorr_ljungbox()

statsmodels.stats.diagnostic.acorr_ljungbox

statsmodels.stats.diagnostic.acorr_ljungbox(x, lags=None, boxpierce=False)

Ljung-Box test for no autocorrelation

Parameters:

x : array_like, 1d data series, regression residuals when used as diagnostic test lags : None, int or array_like If lags is an integer then this is taken to be the largest lag that is included, the test result is reported for all smaller lag length. If lags is a list or array, then all lags are included up to the largest lag in the list, however only the tests for the lags in the list are reported. If lags is None, then the default maxlag is 12*(nobs/100)^{1/4} boxpierce : {False, True} If true, then additional to the results of the Ljung-Box test also the Box-Pierce test results are returned

Returns:

lbvalue : float or array test statistic pvalue : float or array p-value based on chi-square distribution bpvalue : (optionsal), float or array test statistic for Box-Pierce test bppvalue : (optional), float or array p-value based for Box-Pierce test on chi-square distribution

Notes

Ljung-Box and Box-Pierce statistic differ in their scaling of the autocorrelation function. Ljung-Box test is reported to have better small sample properties.

TODO: could be extended to work with more than one series 1d or nd ? axis ? ravel ? needs more testing

??Verification??

Looks correctly sized in Monte Carlo studies. not yet compared to verified values

References

Greene Wikipedia

Examples

see example script