statsmodels.tsa.arima_process.arma_periodogram(ar, ma, worN=None, whole=0) [source]

Periodogram for ARMA process given by lag-polynomials ar and ma

  • 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.
  • w (array) – frequencies
  • sd (array) – periodogram, spectral density


Normalization ?

This uses signal.freqz, which does not use fft. There is a fft version somewhere.

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© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.