statsmodels.tsa.stattools.acovf

statsmodels.tsa.stattools.acovf(x, unbiased=False, demean=True, fft=False, missing='none') [source]

Autocovariance for 1D

Parameters:	x (array) – Time series data. Must be 1d. unbiased (bool) – If True, then denominators is n-k, otherwise n demean (bool) – If True, then subtract the mean x from each element of x fft (bool) – If True, use FFT convolution. This method should be preferred for long time series. missing (str) – A string in [‘none’, ‘raise’, ‘conservative’, ‘drop’] specifying how the NaNs are to be treated.
Returns:	acovf – autocovariance function
Return type:	array

References

[*]	Parzen, E., 1963. On spectral analysis with missing observations and amplitude modulation. Sankhya: The Indian Journal of Statistics, Series A, pp.383-392.