statsmodels.tsa.arima_process.ar2arma¶

statsmodels.tsa.arima_process.
ar2arma
(ar_des, p, q, n=20, mse='ar', start=None)[source]¶ find arma approximation to ar process
This finds the ARMA(p,q) coefficients that minimize the integrated squared difference between the impulse_response functions (MA representation) of the AR and the ARMA process. This does currently not check whether the MA lagpolynomial of the ARMA process is invertible, neither does it check the roots of the AR lagpolynomial.
Parameters: ar_des : array_like
coefficients of original AR lag polynomial, including lag zero
p, q : int
length of desired ARMA lag polynomials
n : int
number of terms of the impuls_response function to include in the objective function for the approximation
mse : string, ‘ar’
not used yet,
Returns: ar_app, ma_app : arrays
coefficients of the AR and MA lag polynomials of the approximation
res : tuple
result of optimize.leastsq
Notes
Extension is possible if we want to match autocovariance instead of impulse response function.
TODO: convert MA lag polynomial, ma_app, to be invertible, by mirroring roots outside the unit intervall to ones that are inside. How do we do this?