Compute the 1-step ahead within-sample forecasts of the observed variables at initial or posterior mode parameter values, or a sample from the prior or the posterior distribution of the parameters. In the event that a sample from the posterior is selected, the number of parameters in the sample is determined by the number of post burn-in posterior draws and the percentage use of posterior draws for impulse responses, variance decompositions and other functions of the parameters. These values are set in the posterior sampling frame on the Options tab.
Alternatively, the 1-step-ahead forecasts can be used to compute prior and posterior predictive checks for the forecast error covariances. In this case, the within-sample 1-step-ahead forecast error covariances are computed for each value of the parameters, drawn from either the prior distribution or the posterior distribution. To check how well the model works relative to its own predictions, the observed covariances can be compared with covariances obtained by simulating data with the model and the parameters.
Additional Information
• | A more detailed description h-steps ahead forecasts can also be found in Section 5.7 of the YADA Manual. |
• | More detailed information about prior and posterior predictive checks can be found in Section 11.16 of the YADA Manual. |
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