Package: RcppSMC 0.2.9

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_0.2.9.tar.gz
RcppSMC_0.2.9.zip(r-4.7-x86_64)RcppSMC_0.2.9.zip(r-4.7-arm64)RcppSMC_0.2.9.zip(r-4.6-x86_64)RcppSMC_0.2.9.zip(r-4.6-arm64)
RcppSMC_0.2.9.tar.gz(r-4.7-arm64)RcppSMC_0.2.9.tar.gz(r-4.7-x86_64)RcppSMC_0.2.9.tar.gz(r-4.6-arm64)RcppSMC_0.2.9.tar.gz(r-4.6-x86_64)
RcppSMC_0.2.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RcppSMC/json (API)

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

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

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

On CRAN:

Conda:

openblascpp

1.70 score 7 scripts 510 downloads 14 exports 3 dependencies

Last updated from:b73d8dce9e. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK158
linux-devel-x86_64OK156
source / vignettesOK212
linux-release-arm64OK163
linux-release-x86_64OK187
windows-devel-arm64OK223
windows-devel-x86_64OK147
windows-release-arm64OK275
windows-release-x86_64OK159
wasm-releaseOK134

Exports:blockpfGaussianOptcompareNCestimatesLinRegLinRegLALinRegLA_adaptnonLinPMMHpfLineartBSpfLineartBSOnlinePlotpfNonlinBSRcppSMC.package.skeletonsimGaussiansimGaussianSSMsimLineartsimNonlin

Dependencies:FKFRcppRcppArmadillo