# statsmodels.tsa.stattools.levinson_durbin¶

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

Levinson-Durbin recursion for autoregressive processes

Parameters
sarray_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

nlagsinteger

largest lag to include in recursion or order of the autoregressive process

isacovboolean

flag to indicate whether the first argument, s, contains the autocovariances or the data series.

Returns
sigma_vfloat

estimate of the error variance ?

arcoefsndarray

estimate of the autoregressive coefficients for a model including nlags

pacfndarray

partial autocorrelation function

sigmandarray

entire sigma array from intermediate result, last value is sigma_v

phindarray

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).