View plots of estimated marginal posterior densities for the DSGE model parameters or selected groups of the VAR parameters of a DSGE-VAR. In the kernel density estimation frame on the Miscellaneous tab you can select how you wish to estimate the posterior densities. The fast methods are (1) Gaussian, and (2) Silverman-type and Sköld-Roberts correction. The slower methods are (3) Sheather-Jones bandwidth, and (4) Bump killing bandwidth. All these methods are based on a Gaussian kernel. For details, see Sköld and Roberts (2003).
The prior densities are also displayed in the graph when they fit. In addition, YADA draws the marginal posterior mode as a solid vertical black line, and the joint posterior mode as a dashed vertical black line. In this situation, the marginal posterior concerns a single parameters, while the joint posterior mode is the joint mode based on the selected posterior mode estimator for the DSGE model parameters.
Additional Information
• | A detailed description about posterior sampling of the DSGE model parameters in the DSGE-VAR model can be found in Section 15.5 of the YADA Manual. |
• | A detailed description about posterior sampling of the VAR parameters in the DSGE-VAR model can be found in Sections 15.4 and 15.6 of the YADA Manual. |
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