Residual Diagnostics

Evaluate model fit and performance

Apps

Econometric ModelerAnalyze and model econometric time series

Functions

inferInfer ARIMA or ARIMAX model residuals or conditional variances
inferInfer innovations of regression models with ARIMA errors
inferInfer conditional variances of conditional variance models
inferInfer vector autoregression model (VAR) innovations
inferInfer vector error-correction (VEC) model innovations

Examples and How To

Perform ARIMA Model Residual Diagnostics Using Econometric Modeler App

Interactively evaluate model assumptions after fitting data to an ARIMA model by performing residual diagnostics.

Perform GARCH Model Residual Diagnostics Using Econometric Modeler App

Interactively evaluate model assumptions after fitting data to a GARCH model by performing residual diagnostics.

Implement Box-Jenkins Model Selection and Estimation Using Econometric Modeler App

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.

Box-Jenkins Model Selection

Use the Box-Jenkins methodology to select an ARIMA model.

Check Fit of Multiplicative ARIMA Model

Conduct goodness of fit checks.

Infer Residuals for Diagnostic Checking

Infer residuals from a fitted ARIMA model.

Infer Conditional Variances and Residuals

Infer conditional variances from a fitted conditional variance model.

Assess State-Space Model Stability Using Rolling Window Analysis

Check whether state-space model is time varying with respect to parameters.

Concepts

Goodness of Fit

Goodness of fit checks can help you identify areas of model inadequacy.

Residual Diagnostics

Check residuals for normality, autocorrelation, and heteroscedasticity.

Check Predictive Performance

Learn how to check the predictive accuracy of a model.

Featured Examples