statsmodels.tsa.stattools.pacf_burg

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

Calculate Burg’s partial autocorrelation estimator.

Parameters

xarray_like

Observations of time series for which pacf is calculated.

nlagsint, optional

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

demeanbool, optional

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

Returns

pacfndarray

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

sigma2ndarray

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

1

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