A note on auxiliary particle filters
From MaRDI portal
Publication:945790
DOI10.1016/j.spl.2008.01.032zbMath1152.62066OpenAlexW2163587350MaRDI QIDQ945790
Arnaud Doucet, Adam M. Johansen
Publication date: 17 September 2008
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.spl.2008.01.032
Related Items
The auxiliary iterated extended Kalman particle filter, A Survey of Sequential Monte Carlo Methods for Economics and Finance, Properties of marginal sequential Monte Carlo methods, The divide-and-conquer sequential Monte Carlo algorithm: theoretical properties and limit theorems, Maximum likelihood estimation of the Markov-switching GARCH model based on a general collapsing procedure, Static-parameter estimation in piecewise deterministic processes using particle Gibbs samplers, Smoothing With Couplings of Conditional Particle Filters, Twisted particle filters, Sequential Monte Carlo smoothing for general state space hidden Markov models, Importance sampling: intrinsic dimension and computational cost, Particle filters and Bayesian inference in financial econometrics, Filtering and estimation for a class of stochastic volatility models with intractable likelihoods, On sequential Monte Carlo, partial rejection control and approximate Bayesian computation, A nonasymptotic theorem for unnormalized Feynman-Kac particle models, Long-term stability of sequential Monte Carlo methods under verifiable conditions, Optimal SIR algorithm vs. fully adapted auxiliary particle filter: a non asymptotic analysis, Nudging the particle filter, Adaptive kernels in approximate filtering of state‐space models, Negative association, ordering and convergence of resampling methods, A statistical approach to estimate state variables in flow-accelerated corrosion problems, Limit theorems for sequential MCMC methods, Ergodicity and accuracy of optimal particle filters for Bayesian data assimilation, Particle learning for Bayesian semi-parametric stochastic volatility model
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Central limit theorem for sequential Monte Carlo methods and its application to Bayesian inference
- Sequential Monte Carlo Methods in Practice
- Particle Filters for Partially Observed Diffusions
- On the auxiliary particle filter
- Filtering via Simulation: Auxiliary Particle Filters
- Sharp Propagation of Chaos Estimates for Feynman–Kac Particle Models
- Monte Carlo strategies in scientific computing
