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-4.7)particlefield_0.0.1.zip(r-4.6)particlefield_0.0.1.zip(r-4.5)
particlefield_0.0.1.tgz(r-4.6-x86_64)particlefield_0.0.1.tgz(r-4.6-arm64)particlefield_0.0.1.tgz(r-4.5-x86_64)particlefield_0.0.1.tgz(r-4.5-arm64)
particlefield_0.0.1.tar.gz(r-4.7-arm64)particlefield_0.0.1.tar.gz(r-4.7-x86_64)particlefield_0.0.1.tar.gz(r-4.6-arm64)particlefield_0.0.1.tar.gz(r-4.6-x86_64)
particlefield_0.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
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:

cpp

2.18 score 3 stars 4 scripts 5 exports 5 dependencies

Last updated from:4cbb2c5c96. Checks:11 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64ERROR161
linux-devel-x86_64ERROR164
source / vignettesOK191
linux-release-arm64ERROR164
linux-release-x86_64ERROR146
macos-release-arm64ERROR136
macos-release-x86_64ERROR219
macos-oldrel-arm64ERROR105
macos-oldrel-x86_64ERROR378
windows-develERROR171
windows-releaseERROR173
windows-oldrelERROR187
wasm-releaseOK145

Exports:approximate_binomial_carbsf_carmcmc_binomial_carprint_graphpsi_car

Dependencies:codalatticeMatrixRcppRcppEigen