statsmodels.tsa.arima_model.ARIMA.score ARIMA.score(params) Compute the score function at params. Notes This is a numerical approximation.

statsmodels.tsa.arima_model.ARIMA.predict ARIMA.predict(params, start=None, end=None, exog=None, typ='linear', dynamic=False) [source] ARIMA model in-sample and out-of-sample prediction Parameters: params : array-like The fitted parameters of the model. start : int, str, or datetime Zero-indexed observation number at which to start forecasting, ie., the first forecast is start. Can also be a date string to parse or a datetime type. end : int, str, or datetime Zero-indexed observation n

statsmodels.tsa.arima_model.ARIMA.loglike_kalman ARIMA.loglike_kalman(params, set_sigma2=True) Compute exact loglikelihood for ARMA(p,q) model by the Kalman Filter.

statsmodels.tsa.arima_model.ARIMA.loglike_css ARIMA.loglike_css(params, set_sigma2=True) Conditional Sum of Squares likelihood function.

statsmodels.tsa.arima_model.ARIMA.initialize ARIMA.initialize() Initialize (possibly re-initialize) a Model instance. For instance, the design matrix of a linear model may change and some things must be recomputed.

statsmodels.tsa.arima_model.ARIMA.loglike ARIMA.loglike(params, set_sigma2=True) Compute the log-likelihood for ARMA(p,q) model Notes Likelihood used depends on the method set in fit

statsmodels.tsa.arima_model.ARIMA.hessian ARIMA.hessian(params) Compute the Hessian at params, Notes This is a numerical approximation.

statsmodels.tsa.arima_model.ARIMA.information ARIMA.information(params) Fisher information matrix of model Returns -Hessian of loglike evaluated at params.

statsmodels.tsa.arima_model.ARIMA.fit ARIMA.fit(start_params=None, trend='c', method='css-mle', transparams=True, solver='lbfgs', maxiter=50, full_output=1, disp=5, callback=None, **kwargs) [source] Fits ARIMA(p,d,q) model by exact maximum likelihood via Kalman filter. Parameters: start_params : array-like, optional Starting parameters for ARMA(p,q). If None, the default is given by ARMA._fit_start_params. See there for more information. transparams : bool, optional Whehter or not to tra

statsmodels.tsa.arima_model.ARIMA.geterrors ARIMA.geterrors(params) Get the errors of the ARMA process. Parameters: params : array-like The fitted ARMA parameters order : array-like 3 item iterable, with the number of AR, MA, and exogenous parameters, including the trend