statsmodels.tsa.stattools.pacf_burg¶

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

Calculate Burg”s partial autocorrelation estimator.

Parameters:¶

xarray_like

Observations of time series for which pacf is calculated.

nlagsint, optional

Number of lags to return autocorrelation for. If not provided, uses min(10 * np.log10(nobs), 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.