class statsmodels.tsa.arima_process.ArmaProcess(ar=None, ma=None, nobs=100)
[source]
Theoretical properties of an ARMA process for specified lag-polynomials
Parameters: |
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Both the AR and MA components must include the coefficient on the zero-lag. In almost all cases these values should be 1. Further, due to using the lag-polynomial representation, the AR parameters should have the opposite sign of what one would write in the ARMA representation. See the examples below.
The ARMA(p,q) process is described by
and the parameterization used in this function uses the lag-polynomial representation,
>>> import numpy as np >>> np.random.seed(12345) >>> arparams = np.array([.75, -.25]) >>> maparams = np.array([.65, .35]) >>> ar = np.r_[1, -ar] # add zero-lag and negate >>> ma = np.r_[1, ma] # add zero-lag >>> arma_process = sm.tsa.ArmaProcess(ar, ma) >>> arma_process.isstationary True >>> arma_process.isinvertible True >>> y = arma_process.generate_sample(250) >>> model = sm.tsa.ARMA(y, (2, 2)).fit(trend='nc', disp=0) >>> model.params array([ 0.79044189, -0.23140636, 0.70072904, 0.40608028])
acf ([lags]) | Theoretical autocorrelation function of an ARMA process |
acovf ([nobs]) | Theoretical autocovariance function of ARMA process |
arma2ar ([lags]) | |
arma2ma ([lags]) | |
from_coeffs ([arcoefs, macoefs, nobs]) | Convenience function to create ArmaProcess from ARMA representation |
from_estimation (model_results[, nobs]) | Convenience function to create an ArmaProcess from the results of an ARMA estimation |
generate_sample ([nsample, scale, distrvs, …]) | Simulate an ARMA |
impulse_response ([leads]) | Get the impulse response function (MA representation) for ARMA process |
invertroots ([retnew]) | Make MA polynomial invertible by inverting roots inside unit circle |
pacf ([lags]) | Partial autocorrelation function of an ARMA process |
periodogram ([nobs]) | Periodogram for ARMA process given by lag-polynomials ar and ma |
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 |
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.tsa.arima_process.ArmaProcess.html