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).