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Prior Sampling

 

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Draw from the normal-inverted Wishart prior distribution of the VAR parameters of all the available DSGE-VAR models. By default, YADA suggest the number of draws to be equal to the number determined by the maximum number of posterior draws to use for prediction option in the posterior sampling frame on the Options tab. The user can change this number within a range from 100  to 50,000  before drawing random numbers from the prior distribution of the parameters.

The prior draws are stored in mat-files in a sub-directory of the base output directory called priordraws. The draws can then be used by the functions where the prior distribution can be used.

 

Additional Information

A detailed description about prior sampling of the VAR parameters in the DSGE-VAR model can be found in Section 15.3 of the YADA Manual.

 

 


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