statsmodels.sandbox.tsa.fftarma.ArmaFft.invpowerspd¶
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ArmaFft.
invpowerspd
(n)[source]¶ autocovariance from spectral density
scaling is correct, but n needs to be large for numerical accuracy maybe padding with zero in fft would be faster without slicing it returns 2-sided autocovariance with fftshift
>>> ArmaFft([1, -0.5], [1., 0.4], 40).invpowerspd(2**8)[:10] array([ 2.08 , 1.44 , 0.72 , 0.36 , 0.18 , 0.09 , 0.045 , 0.0225 , 0.01125 , 0.005625]) >>> ArmaFft([1, -0.5], [1., 0.4], 40).acovf(10) array([ 2.08 , 1.44 , 0.72 , 0.36 , 0.18 , 0.09 , 0.045 , 0.0225 , 0.01125 , 0.005625])