Bayesian time-varying autoregressions : Theory , methods and applications

@inproceedings{Prado2000BayesianTA,
  title={Bayesian time-varying autoregressions : Theory , methods and applications},
  author={Raquel Prado},
  year={2000}
}
We review the class of time-varying autoregressive (TVAR) models and a range of related recent developments of Bayesian time series modelling. Beginning with TVAR models in a Bayesian dynamic linear modelling framework, we review aspects of latent structure analysis, including time-domain decomposition methods that provide inferences on the structure underlying non-stationary time series, and that are now central tools in the time series analyst's toolkit. Recent model extensions that deal with… CONTINUE READING
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Latent structure in non-stationary time series

  • R. Prado
  • Ph.D. Thesis. Duke University,
  • 1998
Highly Influential
15 Excerpts

A reversible jump MCMC sampler for Bayesian analysis of ARMA time series

  • M. M. Barbieri, A. O'Hagan
  • Technical Report. Department of Statistics…
  • 1997
Highly Influential
5 Excerpts

Bayesian Forecasting and Dynamic Linear Models (2nd Edn.)

  • M. West, J. Harrison
  • 1997
Highly Influential
14 Excerpts

Gibbs sampling for state space models

  • C. K. Carter, R. Kohn
  • 1994
Highly Influential
9 Excerpts

Latent structure in non-stationary time series with application in studies of EEG traces

  • M. West, R. Prado, A. Krystal
  • Journal of the American Statistical Association,
  • 1999
Highly Influential
6 Excerpts

Priors and component structures in autoregressive time series models

  • G. Huerta, M. West
  • Journal of the Royal Statistical Society-Series B…
  • 1999
Highly Influential
3 Excerpts

Time varying autoregressions with model order uncertainty

  • R. Prado, G. Huerta
  • Technical Report. Centro de Estad stica y…
  • 1999
Highly Influential
3 Excerpts

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