Corpus ID: 88515107

Flexible Density Tempering Approaches for State Space Models with an Application to Factor Stochastic Volatility Models

  title={Flexible Density Tempering Approaches for State Space Models with an Application to Factor Stochastic Volatility Models},
  author={David Gunawan and Robert Kohn and Chris Carter and Minh-Ngoc Tran},
  journal={arXiv: Methodology},
Duan (2015) propose a tempering or annealing approach to Bayesian inference for time series state space models. In such models the likelihood is often analytically and computationally intractable. Their approach generalizes the annealed importance sampling (AIS) approach of Neal (2001) and DelMoral (2006) when the likelihood can be computed analytically. Annealing is a sequential Monte Carlo approach that moves a collection of parameters and latent state variables through a number of levels… Expand

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