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✨
DESCRIPTION
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-arm64ERROR183
linux-devel-x86_64ERROR182
source / vignettesOK197
linux-release-arm64ERROR197
linux-release-x86_64ERROR169
macos-release-arm64ERROR139
macos-release-x86_64ERROR303
macos-oldrel-arm64ERROR122
macos-oldrel-x86_64ERROR196
windows-develERROR175
windows-releaseERROR193
windows-oldrelERROR158
wasm-releaseOK139

Exports:approximate_binomial_carbsf_carmcmc_binomial_carprint_graphpsi_car

Dependencies:codalatticeMatrixRcppRcppEigen