tsa.stattools.levinson_durbin()

statsmodels.tsa.stattools.levinson_durbin

statsmodels.tsa.stattools.levinson_durbin(s, nlags=10, isacov=False) [source]

Levinson-Durbin recursion for autoregressive processes

Parameters:	s : array_like If isacov is False, then this is the time series. If iasacov is true then this is interpreted as autocovariance starting with lag 0 nlags : integer largest lag to include in recursion or order of the autoregressive process isacov : boolean flag to indicate whether the first argument, s, contains the autocovariances or the data series.
Returns:	sigma_v : float estimate of the error variance ? arcoefs : ndarray estimate of the autoregressive coefficients pacf : ndarray partial autocorrelation function sigma : ndarray entire sigma array from intermediate result, last value is sigma_v phi : ndarray entire phi array from intermediate result, last column contains autoregressive coefficients for AR(nlags) with a leading 1

Notes

This function returns currently all results, but maybe we drop sigma and phi from the returns.

If this function is called with the time series (isacov=False), then the sample autocovariance function is calculated with the default options (biased, no fft).