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