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, Adam M. Johansen, Leah F. South and Ilya Zarubin

RcppSMC_0.2.7.tar.gz
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://cran.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:

openblascpp

1.70 score 7 scripts 284 downloads 14 exports 3 dependencies

Last updated 2 years agofrom:b807d20659. Checks:1 OK, 1 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKJan 19 2025
R-4.5-linux-x86_64NOTEJan 19 2025

Exports:blockpfGaussianOptcompareNCestimatesLinRegLinRegLALinRegLA_adaptnonLinPMMHpfLineartBSpfLineartBSOnlinePlotpfNonlinBSRcppSMC.package.skeletonsimGaussiansimGaussianSSMsimLineartsimNonlin

Dependencies:FKFRcppRcppArmadillo