Package: particlefield 0.0.1

particlefield: Sequential Monte Carlo for Latent Conditional Autoregressive Model

Functions for replicating the results of the latent Gaussian Markov random field experiment of Lindsten, Helske, Vihola (2018), XX. Contains also functions for performing particle Markov chain Monte Carlo estimation of the model parameters.

Authors:Jouni Helske [aut, cre]

particlefield_0.0.1.tar.gz
particlefield_0.0.1.zip(r-4.5)particlefield_0.0.1.zip(r-4.4)particlefield_0.0.1.zip(r-4.3)
particlefield_0.0.1.tgz(r-4.4-x86_64)particlefield_0.0.1.tgz(r-4.4-arm64)particlefield_0.0.1.tgz(r-4.3-x86_64)particlefield_0.0.1.tgz(r-4.3-arm64)
particlefield_0.0.1.tar.gz(r-4.5-noble)particlefield_0.0.1.tar.gz(r-4.4-noble)
particlefield_0.0.1.tgz(r-4.4-emscripten)particlefield_0.0.1.tgz(r-4.3-emscripten)
particlefield.pdf |particlefield.html
particlefield/json (API)

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

Peer review:

Bug tracker:https://github.com/helske/particlefield/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

2.18 score 3 stars 4 scripts 5 exports 5 dependencies

Last updated 3 years agofrom:4cbb2c5c96. Checks:OK: 1 ERROR: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 06 2024
R-4.5-win-x86_64ERRORNov 06 2024
R-4.5-linux-x86_64ERRORNov 06 2024
R-4.4-win-x86_64ERRORNov 06 2024
R-4.4-mac-x86_64ERRORNov 06 2024
R-4.4-mac-aarch64ERRORNov 06 2024
R-4.3-win-x86_64ERRORNov 06 2024
R-4.3-mac-x86_64ERRORNov 06 2024
R-4.3-mac-aarch64ERRORNov 06 2024

Exports:approximate_binomial_carbsf_carmcmc_binomial_carprint_graphpsi_car

Dependencies:codalatticeMatrixRcppRcppEigen