statsmodels.tsa.arima_process.ArmaProcess.periodogram
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ArmaProcess.periodogram(nobs=None)
[source] -
periodogram for ARMA process given by lag-polynomials ar and ma
Parameters: ar : array_like
autoregressive lag-polynomial with leading 1 and lhs sign
ma : array_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: w : array
frequencies
sd : array
periodogram, spectral density
Notes
Normalization ?
This uses signal.freqz, which does not use fft. There is a fft version somewhere.
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