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


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


bds_stat : float

The BDS statistic

pvalue : float

The p-values associated with the BDS statistic


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)})