tsa.stattools.pacf()

statsmodels.tsa.stattools.pacf

statsmodels.tsa.stattools.pacf(x, nlags=40, method='ywunbiased', alpha=None) [source]

Partial autocorrelation estimated

Parameters:

x : 1d array observations of time series for which pacf is calculated nlags : int largest lag for which pacf is returned method : ‘ywunbiased’ (default) or ‘ywmle’ or ‘ols’ specifies which method for the calculations to use: yw or ywunbiased : yule walker with bias correction in denominator for acovf ywm or ywmle : yule walker without bias correction ols - regression of time series on lags of it and on constant ld or ldunbiased : Levinson-Durbin recursion with bias correction ldb or ldbiased : Levinson-Durbin recursion without bias correction alpha : scalar, optional If a number is given, the confidence intervals for the given level are returned. For instance if alpha=.05, 95 % confidence intervals are returned where the standard deviation is computed according to 1/sqrt(len(x))

Returns:

pacf : 1d array partial autocorrelations, nlags elements, including lag zero confint : array, optional Confidence intervals for the PACF. Returned if confint is not None.

Notes

This solves yule_walker equations or ols for each desired lag and contains currently duplicate calculations.