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 not check whether the MA lag polynomial of the ARMA process is invertible, neither does it check the roots of the AR lag polynomial.
- Parameters:
- ar_desnumpy:array_like
The coefficients of original AR lag polynomial, including lag zero.
- p
int
The length of desired AR lag polynomials.
- q
int
The length of desired MA lag polynomials.
- n
int
The number of terms of the impulse_response function to include in the objective function for the approximation.
- mse
str
, ‘ar’ Not used.
- start
ndarray
Initial values to use when finding the approximation.
- Returns:
- ar_app
ndarray
The coefficients of the AR lag polynomials of the approximation.
- ma_app
ndarray
The coefficients of the MA lag polynomials of the approximation.
- res
tuple
The result of optimize.leastsq.
- ar_app
Notes
Extension is possible if we want to match autocovariance instead of impulse response function.