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 for a model including nlags

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)

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).