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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.

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)

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Install

install.packages('RcppSMC')

Monthly Downloads

316

Version

0.2.1

License

GPL (>= 2)

Maintainer

Dirk Eddelbuettel

Last Published

March 18th, 2018

Functions in RcppSMC (0.2.1)

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)