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.

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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.

Authors

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

License

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)
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Details

Type Package
Date 2017-08-27
License GPL (>= 2)
LazyLoad yes
LinkingTo Rcpp, RcppArmadillo
LazyData true
NeedsCompilation yes
Packaged 2017-08-28 11:18:51.018351 UTC; edd
Repository CRAN
Date/Publication 2017-08-28 11:36:00 UTC

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