statsmodels.tsa.tests.test_arima_process.ArmaFft¶
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class
statsmodels.tsa.tests.test_arima_process.ArmaFft(ar, ma, n)[source]¶ fft tools for arma processes
This class contains several methods that are providing the same or similar returns to try out and test different implementations.
Notes
TODO: check whether we don’t want to fix maxlags, and create new instance if maxlag changes. usage for different lengths of timeseries ? or fix frequency and length for fft
check default frequencies w, terminology norw n_or_w
some ffts are currently done without padding with zeros
returns for spectral density methods needs checking, is it always the power spectrum hw*hw.conj()
normalization of the power spectrum, spectral density: not checked yet, for example no variance of underlying process is used
Methods¶
__init__(ar, ma, n) |
|
acf([nobs]) |
theoretical autocorrelation function of an ARMA process |
acf2spdfreq(acovf[, nfreq, w]) |
not really a method |
acovf([nobs]) |
theoretical autocovariance function of ARMA process |
arma2ar([nobs]) |
|
arma2ma([nobs]) |
|
fftar([n]) |
Fourier transform of AR polynomial, zero-padded at end to n |
fftarma([n]) |
Fourier transform of ARMA polynomial, zero-padded at end to n |
fftma(n) |
Fourier transform of MA polynomial, zero-padded at end to n |
filter(x) |
filter a timeseries with the ARMA filter |
filter2(x[, pad]) |
filter a time series using fftconvolve3 with ARMA filter |
from_coeffs(arcoefs, macoefs[, nobs]) |
Create ArmaProcess instance from coefficients of the lag-polynomials |
from_estimation(model_results[, nobs]) |
Create ArmaProcess instance from ARMA estimation results |
generate_sample([nsample, scale, distrvs, ...]) |
generate ARMA samples |
impulse_response([nobs]) |
get the impulse response function (MA representation) for ARMA process |
invertroots([retnew]) |
make MA polynomial invertible by inverting roots inside unit circle |
invpowerspd(n) |
autocovariance from spectral density |
pacf([nobs]) |
partial autocorrelation function of an ARMA process |
pad(maxlag) |
construct AR and MA polynomials that are zero-padded to a common length |
padarr(arr, maxlag[, atend]) |
pad 1d array with zeros at end to have length maxlag |
periodogram([nobs]) |
periodogram for ARMA process given by lag-polynomials ar and ma |
plot4([fig, nobs, nacf, nfreq]) |
|
spd(npos) |
raw spectral density, returns Fourier transform |
spddirect(n) |
power spectral density using padding to length n done by fft |
spdmapoly(w[, twosided]) |
ma only, need division for ar, use LagPolynomial |
spdpoly(w[, nma]) |
spectral density from MA polynomial representation for ARMA process |
spdroots(w) |
spectral density for frequency using polynomial roots |
spdroots_(arroots, maroots, w) |
spectral density for frequency using polynomial roots |
spdshift(n) |
power spectral density using fftshift |
Attributes¶
arroots |
Roots of autoregressive lag-polynomial |
isinvertible |
Arma process is invertible if MA roots are outside unit circle |
isstationary |
Arma process is stationary if AR roots are outside unit circle |
maroots |
Roots of moving average lag-polynomial |