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We propose a new methodology for designing flexible proposal densities for the joint posterior density of parameters and states in a nonlinear non-Gaussian state space model. We show that a highly efficient Bayesian procedure emerges when these proposal densities are used in an independent...
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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 …
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