statsmodels.sandbox.tsa.fftarma.ArmaFft.periodogram
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ArmaFft.periodogram(nobs=None)
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Periodogram for ARMA process given by lag-polynomials ar and ma
Parameters: |
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ar (array_like) – autoregressive lag-polynomial with leading 1 and lhs sign
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ma (array_like) – moving average lag-polynomial with leading 1
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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
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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.
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Returns: |
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w (array) – frequencies
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sd (array) – periodogram, spectral density
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Notes
Normalization ?
This uses signal.freqz, which does not use fft. There is a fft version somewhere.