Elias T. Krainski

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In this paper we propose a computational framework to perform approximate Bayesian inference in linear and generalized linear dynamic models based on the Integrated Nested Laplace Approximation (INLA) approach, which overcomes some limitations of computational tools presently available in the dynamic modeling literature. We show how to formulate specific(More)
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