View plots of estimated marginal prior densities. If the DSGE model has parameters that are a function of the estimated parameters (determined in the file with parameters to update), YADA can optionally include the implied marginal prior densities of these parameters: YADA refers to this as a simulated prior in the graph (see screenshot below). In the kernel density estimation frame on the Miscellaneous tab you can select how you wish to estimate the prior densities. The default is the grid density estimate. This means that YADA sets up a grid based on the data in the prior distribution file. The alternative is to a kernel density estimate. For this case YADA generates 5,000 random draws from the prior distribution and estimates the densities from this data.
In addition to the estimated density, YADA will also draw the initial value of the parameter as a solid horizontal black line.
Additional Information
• | A more detailed description about the prior densities can be found in Section 4.2 of the YADA Manual. |
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