RcppSMC v0.2.1

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Rcpp Bindings for Sequential Monte Carlo

R access to the Sequential Monte Carlo Template Classes by Johansen <doi:10.18637/jss.v030.i06> is provided. At present, four additional examples have been added, and the first example from the JSS paper has been extended. Further integration and extensions are planned.

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RcppSMC Build Status License CRAN Downloads

Rcpp Bindings for Sequential Monte Carlo

Summary

This package provides R with access to the Sequential Monte Carlo Template Classes by Johansen (Journal of Statistical Software, 2009, v30, i6).

At present, four additional examples have been added, and the first example from the JSS paper has been extended. Further integration and extensions are planned.

For support and discussion please make us of the rcppsmc mailing list.

Authors

Dirk Eddelbuettel, Adam M. Johansen and Leah F. South

License

GPL (>= 2)

Functions in RcppSMC

Name Description
nonLinPMMH Particle marginal Metropolis-Hastings for a non-linear state space model.
pfLineartBS Particle Filter Example
LinReg Simple Linear Regression
simNonlin Simulates from a simple nonlinear state space model.
pfNonlinBS Nonlinear Bootstrap Particle Filter (Univariate Non-Linear State Space Model)
blockpfGaussianOpt Block Sampling Particle Filter (Linear Gaussian Model; Optimal Proposal)
radiata Radiata pine dataset (linear regression example)
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Details

Type Package
Date 2018-03-18
License GPL (>= 2)
LazyLoad yes
LinkingTo Rcpp, RcppArmadillo
LazyData true
NeedsCompilation yes
Packaged 2018-03-18 19:40:05.890731 UTC; edd
Repository CRAN
Date/Publication 2018-03-18 19:53:57 UTC

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