-dimensional spaces of latent variables. Direct sampling from the approximate posterior is possible. The new technique is applied to …

used in importance sampling for model estimation, model selection and model combination. The procedure is fully automatic …

Two Bayesian sampling schemes are outlined to estimate a K-state Markov switching model with time-varying transition …. Identification issues are addressed with random permutation sampling. In terms of efficiency, the extension to the difference in … random utility specification in combination with random permutation sampling performs best. We apply the method to estimate a …

A class of adaptive sampling methods is introduced for efficient posterior and predictive simulation. The proposed … target and mixture is minimized. We label this approach Mixture of t by Importance Sampling and Expectation Maximization …, we introduce a permutation-augmented MitISEM approach, for importance sampling from posterior distributions in mixture …

A class of adaptive sampling methods is introduced for efficient posterior and predictive simulation. The proposed … between target and mixture is minimized. We label this approach Mixture of t by Importance Sampling and Expectation …, we introduce a permutation-augmented MitISEM approach, for importance sampling from posterior distributions in mixture …

In this note, we build upon the asymptotic theory for GARCH processes, considering the general class of augmented GARCH …