Sequential Monte Carlo as Approximate Sampling : bounds , adaptive resampling via ∞-ESS , and an application to Particle Gibbs JONATHAN

@inproceedings{Huggins2017SequentialMC,
  title={Sequential Monte Carlo as Approximate Sampling : bounds , adaptive resampling via ∞-ESS , and an application to Particle Gibbs JONATHAN},
  author={H. Huggins and Daniel M. Roy},
  year={2017}
}
Sequential Monte Carlo (SMC) algorithms were originally designed for estimating intractable conditional expectations within state-space models, but are now routinely used to generate approximate samples in the context of general-purpose Bayesian inference. In particular, SMC algorithms are often used as subroutines within larger Monte Carlo schemes, and in… CONTINUE READING