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The aim of these notes is to revisit sequential Monte Carlo (SMC) sampling. SMC sampling is a powerful simulation tool …
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Econometric analysis requires filtering techniques that are adapted to cater to data sequences that are short and that have strong trends. Whereas the economists have tended to conduct their analyses in the time domain, the engineers have emphasised the frequency domain. This paper places its...
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We consider likelihood inference and state estimation by means of importance sampling for state space models with a … are presented that lead to a more effective implementation of importance sampling for state space models. An illustration …
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instance of precision-based sampling methods that operate on the inverse variance-covariance matrix of the states (also known … other instances of precision-based sampling, computational gains are considerable. Relevant applications include trend …
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We consider the dynamic factor model where the loading matrix, the dynamic factors and the disturbances are treated as latent stochastic processes. We present empirical Bayes methods that enable the efficient shrinkage-based estimation of the loadings and the factors. We show that our estimates...
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