# RcppSMC v0.2.0

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## Rcpp Bindings for Sequential Monte Carlo

R access to the Sequential Monte Carlo Template Classes by Johansen (Journal of Statistical Software, 2009, v30, i6) is provided. At present, two additional examples have been added, and the first example from the JSS paper has been extended. Further integration and extensions are planned.

## RcppSMC

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.

### Authors

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

GPL (>= 2)

## Functions in RcppSMC

 Name Description simNonlin Simulates from a simple nonlinear state space model. LinReg Simple Linear Regression blockpfGaussianOpt Block Sampling Particle Filter (Linear Gaussian Model; Optimal Proposal) nonLinPMMH Particle marginal Metropolis-Hastings for a non-linear state space model. pfLineartBS Particle Filter Example pfNonlinBS Nonlinear Bootstrap Particle Filter (Univariate Non-Linear State Space Model) radiata Radiata pine dataset (linear regression example) No Results!