Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models

@article{Kastner2014AncillaritysufficiencyIS,
  title={Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models},
  author={Gregor Kastner and Sylvia Fr{\"u}hwirth-Schnatter},
  journal={Computational Statistics & Data Analysis},
  year={2014},
  volume={76},
  pages={408-423}
}
Bayesian inference for stochastic volatility models using MCMC methods highly depends on actual parameter values in terms of sampling efficiency. While draws from the posterior utilizing the standard centered parameterization break down when the volatility of volatility parameter in the latent state equation is small, non-centered versions of the model show deficiencies for highly persistent latent variable series. The novel approach of ancillarity-sufficiency interweaving has recently been… CONTINUE READING
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Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models

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