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YADA Version 4.00

 

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Released on 31/10/2016:

The iterated parameter estimates function supports saving the values of the original parameters to mat-file for a certain iteration.
The predictive distribution functions for DSGE, BVAR and DSGE-VAR models now support several data set, called actuals, to represent the observed data.
Added tools for utilizing the parallel computing toolbox. Conditional variance decompositions for DSGE models and variance decompositions for DSGE and DSGE-VAR models are now also supported if the number of allowed computations threads is at least equal to 2. Parallel computing in YADA can be opened and closed from the File menu.

 

 


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