statsmodels.tsa.arima_process.arma_periodogram¶
-
statsmodels.tsa.arima_process.arma_periodogram(ar, ma, worN=None, whole=0)[source]¶ Periodogram for ARMA process given by lag-polynomials ar and ma
- Parameters
- ararray_like
autoregressive lag-polynomial with leading 1 and lhs sign
- maarray_like
moving average lag-polynomial with leading 1
- worN{None, int}, optional
option for scipy.signal.freqz (read “w or N”) If None, then compute at 512 frequencies around the unit circle. If a single integer, the compute at that many frequencies. Otherwise, compute the response at frequencies given in worN
- whole{0,1}, optional
options for scipy.signal.freqz Normally, frequencies are computed from 0 to pi (upper-half of unit-circle. If whole is non-zero compute frequencies from 0 to 2*pi.
- Returns
- warray
frequencies
- sdarray
periodogram, spectral density
Notes
Normalization ?
This uses signal.freqz, which does not use fft. There is a fft version somewhere.