|Econometric Modeler||Analyze and model econometric time series|
|Infer ARIMA or ARIMAX model residuals or conditional variances|
|Infer innovations of regression models with ARIMA errors|
|Infer conditional variances of conditional variance models|
|Infer vector autoregression model (VAR) innovations|
|Infer vector error-correction (VEC) model innovations|
Examples and How To
Interactively evaluate model assumptions after fitting data to an ARIMA model by performing residual diagnostics.
Interactively evaluate model assumptions after fitting data to a GARCH model by performing residual diagnostics.
Interactively implement the Box-Jenkins methodology to select the appropriate number of lags for a conditional mean model. Then, fit the model to data and export the estimated model to the command line to generate forecasts.
Use the Box-Jenkins methodology to select an ARIMA model.
Conduct goodness of fit checks.
Infer residuals from a fitted ARIMA model.
Infer conditional variances from a fitted conditional variance model.
Check whether state-space model is time varying with respect to parameters.