statsmodels.tsa.arima_process.arma_acovf#

statsmodels.tsa.arima_process.arma_acovf(ar, ma, nobs=10, sigma2=1, dtype=None)[source]#

Theoretical autocovariances of stationary ARMA processes

Parameters:
ararray_like, 1d

The coefficients for autoregressive lag polynomial, including zero lag.

maarray_like, 1d

The coefficients for moving-average lag polynomial, including zero lag.

nobsint

The number of terms (lags plus zero lag) to include in returned acovf.

sigma2float

Variance of the innovation term.

dtypestr, optional

Numpy dtype to use for the output. If None (the default), the dtype is inferred from the common type of ar, ma, and sigma2.

Returns:
ndarray

The autocovariance of ARMA process given by ar, ma.

See also

arma_acf

Autocorrelation function for ARMA processes.

acovf

Sample autocovariance estimation.

References