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.
Readme
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)
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) | |
| No Results! | ||
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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 |
| imports | methods , Rcpp (>= 0.11.0) |
| linkingto | RcppArmadillo |
| Contributors | Dirk Eddelbuettel, Adam Johansen, Leah South |
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