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The authors consider a dynamic probit model where the coefficients follow a first-order Markov process. An exact Gibbs sampler for Bayesian analysis is presented for the model using the data augmentation approach and the forward filtering backward sampling algorithm for dynamic linear models. The authors discuss how our approach can be used for dynamic probit models as well as its generalizations...
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