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RcppSMC  

Rcpp Bindings for Sequential Monte Carlo
View on CRAN: Click here


Download and install RcppSMC package within the R console
Install from CRAN:
install.packages("RcppSMC")

Install from Github:
library("remotes")
install_github("cran/RcppSMC")

Install by package version:
library("remotes")
install_version("RcppSMC", "0.2.7")



Attach the package and use:
library("RcppSMC")
Maintained by
Dirk Eddelbuettel
[Scholar Profile | Author Map]
First Published: 2012-03-22
Latest Update: 2023-03-22
Description:
R access to the Sequential Monte Carlo Template Classes by Johansen 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.
How to cite:
Dirk Eddelbuettel (2012). RcppSMC: Rcpp Bindings for Sequential Monte Carlo. R package version 0.2.7, https://cran.r-project.org/web/packages/RcppSMC. Accessed 26 Mar. 2025.
Previous versions and publish date:
0.1.0 (2012-03-22 07:58), 0.1.1 (2012-05-15 08:38), 0.1.2 (2014-02-06 19:17), 0.1.3 (2014-05-02 07:07), 0.1.4 (2014-05-02 15:38), 0.1.5 (2017-03-03 21:13), 0.2.0 (2017-08-28 13:36), 0.2.1 (2018-03-18 20:53), 0.2.2 (2020-08-30 16:40), 0.2.3 (2021-02-10 15:10), 0.2.4 (2021-09-03 00:00), 0.2.5 (2021-09-09 16:00), 0.2.6 (2021-12-18 13:40)
Other packages that cited RcppSMC R package
View RcppSMC citation profile
Other R packages that RcppSMC depends, imports, suggests or enhances
Complete documentation for RcppSMC
Functions, R codes and Examples using the RcppSMC R package
Some associated functions: LinReg . blockpfGaussianOpt . nonLinPMMH . pfLineartBS . pfNonlinBS . radiata . simNonlin . 
Some associated R codes: LinReg.R . LinRegLA.R . LinRegLA_adapt.R . RcppExports.R . bspfGaussianOptimal.R . nonLinPMMH.R . pfLineartBS.R . pfNonlinBS.R . plugin.R . simGaussian.R . simLineart.R . simNonlin.R .  Full RcppSMC package functions and examples
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