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Model Comparisons

Tests for nested models and information criteria

Functions

aicbicAkaike or Bayesian information criteria
lmtestLagrange multiplier test of model specification
lratiotestLikelihood ratio test of model specification
waldtestWald test of model specification
arma2arConvert ARMA model to AR model
arma2maConvert ARMA model to MA model
var2vecConvert VAR model to VEC model
vec2varConvert VEC model to VAR model

Examples and How To

Compare GARCH Models Using Likelihood Ratio Test

Conduct a likelihood ratio test to choose the number of lags in a GARCH model.

Conduct a Lagrange Multiplier Test

Compare the fit of a restricted model against an unrestricted model by testing whether the gradient of the loglikelihood function of the unrestricted model, evaluated at the restricted maximum likelihood estimates (MLEs), is significantly different from zero.

Conduct a Wald Test

Compare the fit of a restricted model against an unrestricted model by testing whether the restriction function, evaluated at the unrestricted maximum likelihood estimates (MLEs), is significantly different from zero.

Choose ARMA Lags Using BIC

Select ARMA model using information criteria.

Likelihood Ratio Test for Conditional Variance Models

Fit two competing, conditional variance models to data, and then compare their fits using a likelihood ratio test.

Classical Model Misspecification Tests

This example shows the use of the likelihood ratio, Wald, and Lagrange multiplier tests.

Compare Conditional Variance Models Using Information Criteria

Compare the fits of several conditional variance models using AIC and BIC.

Choose State-Space Model Specification Using Backtesting

Choose the state-space model specification with the best predictive performance using a rolling window.

Concepts

Model Comparison Tests

Learn the mechanics behind the likelihood ratio, Lagrange multiplier, and Wald model-comparison tests.

Information Criteria

Learn about the AIC and BIC measures of model-fit.

Select Regression Model with ARIMA Errors

Learn how to select an appropriate regression model with ARIMA errors.

Rolling-Window Analysis of Time-Series Models

Estimate explicitly and implicitly defined state-space models using a rolling window.

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