Variance estimation in the particle filter

@article{Lee2015VarianceEI,
  title={Variance estimation in the particle filter},
  author={Anthony Lee and Nick Whiteley},
  journal={arXiv: Computation},
  year={2015}
}
This paper concerns numerical assessment of Monte Carlo error in particle filters. We show that by keeping track of certain key features of the genealogical structure arising from resampling operations, it is possible to estimate variances of a number of standard Monte Carlo approximations which particle filters deliver. All our estimators can be computed from a single run of a particle filter with no further simulation. We establish that as the number of particles grows, our estimators are… Expand
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