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Marginal Posterior Densities

 

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View plots of estimated marginal posterior and 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 marginal posterior and implied prior densities of these parameters. 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.

 

 


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