statsmodels.tsa.stattools.pacf_burg

statsmodels.tsa.stattools.pacf_burg(x, nlags=None, demean=True)[source]

Calculate Burg’s partial autocorrelation estimator.

Parameters:

x : array_like

Observations of time series for which pacf is calculated.

nlags : int, optional

Number of lags to compute the partial autocorrelations. If omitted, uses the smaller of 10(log10(nobs)) or nobs - 1.

demean : bool, optional

Flag indicating to demean that data. Set to False if x has been previously demeaned.

Returns:

pacf : ndarray

Partial autocorrelations for lags 0, 1, …, nlag.

sigma2 : ndarray

Residual variance estimates where the value in position m is the residual variance in an AR model that includes m lags.

See also

statsmodels.tsa.stattools.pacf
Partial autocorrelation estimation.
statsmodels.tsa.stattools.pacf_yw
Partial autocorrelation estimation using Yule-Walker.
statsmodels.tsa.stattools.pacf_ols
Partial autocorrelation estimation using OLS.

References

[R186]Brockwell, P.J. and Davis, R.A., 2016. Introduction to time series and forecasting. Springer.