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nimbleSMC (version 0.11.0)

Sequential Monte Carlo Methods for 'nimble'

Description

Includes five particle filtering algorithms for use with state space models in the 'nimble' system: 'Auxiliary', 'Bootstrap', 'Ensemble Kalman filter', 'Iterated Filtering 2', and 'Liu-West', as described in Michaud et al. (2021), . A full User Manual is available at .

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Install

install.packages('nimbleSMC')

Monthly Downloads

624

Version

0.11.0

License

BSD_3_clause + file LICENSE | GPL (>= 2)

Issues

5

Pull Requests

0

Stars

4

Forks

2

Maintainer

Christopher Paciorek

Last Published

September 10th, 2023

Functions in nimbleSMC (0.11.0)

SMCsamplers

Particle Filtering MCMC Sampling Algorithms
buildEnsembleKF

Create an Ensemble Kalman filter algorithm to sample from latent states.
buildAuxiliaryFilter

Create an auxiliary particle filter algorithm to estimate log-likelihood.
buildIteratedFilter2

Create an IF2 algorithm.
buildLiuWestFilter

Create a Liu and West particle filter algorithm.
buildBootstrapFilter

Create a bootstrap particle filter algorithm to estimate log-likelihood.