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Residual Diagnostics

Evaluate model fit and performance

Functions

infer Infer ARIMA or ARIMAX model residuals or conditional variances
infer Infer innovations of regression models with ARIMA errors
infer Infer conditional variances of conditional variance models

Examples and How To

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.

Time Series Regression VI: Residual Diagnostics

This example shows how to evaluate model assumptions and investigate respecification opportunities by examining the series of residuals.

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.

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