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-4.5-x86_64)particlefield_0.0.1.tgz(r-4.5-arm64)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'))

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

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

On CRAN:

Conda-Forge:

cpp

2.18 score 3 stars 4 scripts 5 exports 5 dependencies

Last updated 4 years agofrom:4cbb2c5c96. Checks:1 OK, 11 ERROR. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 06 2025
R-4.5-win-x86_64ERRORMar 06 2025
R-4.5-mac-x86_64ERRORMar 06 2025
R-4.5-mac-aarch64ERRORMar 06 2025
R-4.5-linux-x86_64ERRORMar 06 2025
R-4.4-win-x86_64ERRORMar 06 2025
R-4.4-mac-x86_64ERRORMar 06 2025
R-4.4-mac-aarch64ERRORMar 06 2025
R-4.4-linux-x86_64ERRORMar 06 2025
R-4.3-win-x86_64ERRORMar 06 2025
R-4.3-mac-x86_64ERRORMar 06 2025
R-4.3-mac-aarch64ERRORMar 06 2025

Exports:approximate_binomial_carbsf_carmcmc_binomial_carprint_graphpsi_car

Dependencies:codalatticeMatrixRcppRcppEigen