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YADA Version 1.60

 

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Released on 12/03/2009:

Conditional correlations.
Save state-space matrices to mat-file.
Save parameter covariance matrix to mat-file when it has been estimated from posterior draws.
Use own parameter covariance matrix for the inverse Hessian matrix of the proposal density for the random-walk Metropolis algorithm.
Display posterior densities of parameters that are a function of the estimated parameters.
Results on such parameters are now written into the results files of the posterior mode and posterior sampling functions.
Impulse responses for shock groups.
View plots of conditioning variables.
Kernel density estimates of the marginal predictive distributions for each time period.
Additional error messages from AiM are now reported.

 

 


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