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scikits.statsmodels.tsa.arima_process.ArmaProcess

class scikits.statsmodels.tsa.arima_process.ArmaProcess(ar, ma, nobs=None)[source]

represents an ARMA process for given lag-polynomials

This is a class to bring together properties of the process. It does not do any estimation or statistical analysis.

maybe needs special handling for unit roots

Methods

acf([nobs]) theoretical autocovariance function of ARMA process
acovf([nobs]) theoretical autocovariance function of ARMA process
ar_roots() roots of autoregressive lag-polynomial
arma2ar([nobs])
arma2ma([nobs])
from_coeffs(arcoefs, macoefs[, nobs]) create ArmaProcess instance from coefficients of the lag-polynomials
from_estimation(model_results[, nobs]) create ArmaProcess instance from estimation results
generate_sample([size, 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
isinvertible() Arma process is invertible if MA roots are outside unit circle
isstationary() Arma process is stationary if AR roots are outside unit circle
ma_roots() roots of moving average lag-polynomial
pacf([nobs]) partial autocorrelation function of an ARMA process
periodogram([nobs]) periodogram for ARMA process given by lag-polynomials ar and ma

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