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We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...
Persistent link: https://www.econbiz.de/10011272583
This discussion paper resulted in a publication in the 'Journal of Econometrics', 2013, 177(2), 213-232.<P> We propose a Bayesian combination approach for multivariate predictive densities which relies upon a distributional state space representation of the combination weights. Several...</p>
Persistent link: https://www.econbiz.de/10011255873
Using a Bayesian framework this paper provides a multivariate combination approach to prediction based on a distributional state space representation of predictive densities from alternative models. In the proposed approach the model set can be incomplete. Several multivariate time-varying...
Persistent link: https://www.econbiz.de/10008838629
Using a Bayesian framework this paper provides a multivariate combination approach to prediction based on a distributional state space representation of predictive densities from alternative models. In the proposed approach the model set can be incomplete. Several multivariate time-varying...
Persistent link: https://www.econbiz.de/10011256724