tsa.stattools.bds()

statsmodels.tsa.stattools.bds

statsmodels.tsa.stattools.bds(x, max_dim=2, epsilon=None, distance=1.5) [source]

Calculate the BDS test statistic for independence of a time series

Parameters:	x : 1d array observations of time series for which bds statistics is calculated max_dim : integer maximum embedding dimension epsilon : scalar, optional the threshold distance to use in calculating the correlation sum distance : scalar, optional if epsilon is omitted, specifies the distance multiplier to use when computing it
Returns:	bds_stat : float The BDS statistic pvalue : float The p-values associated with the BDS statistic

Notes

The null hypothesis of the test statistic is for an independent and identically distributed (i.i.d.) time series, and an unspecified alternative hypothesis.

This test is often used as a residual diagnostic.

The calculation involves matrices of size (nobs, nobs), so this test will not work with very long datasets.

Implementation conditions on the first m-1 initial values, which are required to calculate the m-histories: x_t^m = (x_t, x_{t-1}, ... x_{t-(m-1)})