Logo

statsmodels.tsa.arima_model.ARMA

class statsmodels.tsa.arima_model.ARMA(endog, exog=None, dates=None, freq=None)[source]

Autoregressive Moving Average ARMA(p,q) Model

Parameters:

endog : array-like

The endogenous variable.

exog : array-like, optional

An optional arry of exogenous variables. This should not include a constant or trend. You can specify this in the fit method.

Methods

fit(order[, start_params, trend, method, ...]) Fits ARMA(p,q) model using exact maximum likelihood via Kalman filter.
geterrors(params) Get the errors of the ARMA process.
hessian(params) Compute the Hessian at params,
information(params) Fisher information matrix of model
initialize() Initialize (possibly re-initialize) a Model instance.
loglike(params) Compute the log-likelihood for ARMA(p,q) model
loglike_css(params) Conditional Sum of Squares likelihood function.
loglike_kalman(params) Compute exact loglikelihood for ARMA(p,q) model using the Kalman Filter.
predict(params[, start, end, exog]) In-sample and out-of-sample prediction.
score(params) Compute the score function at params.

Attributes

endog_names
exog_names

Previous topic

statsmodels.tsa.ar_model.ARResults.tvalues

Next topic

statsmodels.tsa.arima_model.ARMA.fit

This Page