Package: RcppSMC 0.2.7

Dirk Eddelbuettel

RcppSMC: 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.

Authors:Dirk Eddelbuettel [aut, cre], Adam M. Johansen [aut], Leah F. South [aut], Ilya Zarubin [aut]

RcppSMC_0.2.7.tar.gz
RcppSMC_0.2.7.zip(r-4.5)RcppSMC_0.2.7.zip(r-4.4)RcppSMC_0.2.7.zip(r-4.3)
RcppSMC_0.2.7.tgz(r-4.4-x86_64)RcppSMC_0.2.7.tgz(r-4.4-arm64)RcppSMC_0.2.7.tgz(r-4.3-x86_64)RcppSMC_0.2.7.tgz(r-4.3-arm64)
RcppSMC_0.2.7.tar.gz(r-4.5-noble)RcppSMC_0.2.7.tar.gz(r-4.4-noble)
RcppSMC_0.2.7.tgz(r-4.4-emscripten)RcppSMC_0.2.7.tgz(r-4.3-emscripten)
RcppSMC.pdf |RcppSMC.html✨
RcppSMC/json (API)
NEWS

# Install 'RcppSMC' in R:
install.packages('RcppSMC', repos = c('https://rcppsmc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/rcppsmc/rcppsmc/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

particle-filterrcppsequantial-monte-carlo

5.18 score 25 stars 7 scripts 297 downloads 14 exports 3 dependencies

Last updated 29 days agofrom:a0dd531d7c. Checks:OK: 4 NOTE: 5. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 24 2024
R-4.5-win-x86_64NOTEOct 24 2024
R-4.5-linux-x86_64NOTEOct 24 2024
R-4.4-win-x86_64NOTEOct 24 2024
R-4.4-mac-x86_64NOTEOct 24 2024
R-4.4-mac-aarch64NOTEOct 24 2024
R-4.3-win-x86_64OKOct 24 2024
R-4.3-mac-x86_64OKOct 24 2024
R-4.3-mac-aarch64OKOct 24 2024

Exports:blockpfGaussianOptcompareNCestimatesLinRegLinRegLALinRegLA_adaptnonLinPMMHpfLineartBSpfLineartBSOnlinePlotpfNonlinBSRcppSMC.package.skeletonsimGaussiansimGaussianSSMsimLineartsimNonlin

Dependencies:FKFRcppRcppArmadillo