statsmodels.regression.linear_model.burg

statsmodels.regression.linear_model.burg(endog, order=1, demean=True)[source]

Compute Burg’s AP(p) parameter estimator.

Parameters
endogarray_like

The endogenous variable.

orderint, optional

Order of the AR. Default is 1.

demeanbool, optional

Flag indicating to subtract the mean from endog before estimation.

Returns
rhondarray

The AR(p) coefficients computed using Burg’s algorithm.

sigma2float

The estimate of the residual variance.

See also

yule_walker

Estimate AR parameters using the Yule-Walker method.

Notes

AR model estimated includes a constant that is estimated using the sample mean (see [1]). This value is not reported.

References

1

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

Examples

>>> import statsmodels.api as sm
>>> from statsmodels.datasets.sunspots import load
>>> data = load()
>>> rho, sigma2 = sm.regression.linear_model.burg(data.endog, order=4)
>>> rho
array([ 1.30934186, -0.48086633, -0.20185982,  0.05501941])
>>> sigma2
271.2467306963966