Package: mrfse 0.4.2

mrfse: Markov Random Field Structure Estimator

Three algorithms for estimating a Markov random field structure.Two of them are an exact version and a simulated annealing version of a penalized maximum conditional likelihood method similar to the Bayesian Information Criterion. These algorithm are described in Frondana (2016) <doi:10.11606/T.45.2018.tde-02022018-151123>.The third one is a greedy algorithm, described in Bresler (2015) <doi:10.1145/2746539.2746631).

Authors:Rodrigo Carvalho [aut, cre], Florencia Leonardi [rev, ths]

mrfse_0.4.2.tar.gz
mrfse_0.4.2.zip(r-4.7)mrfse_0.4.2.zip(r-4.6)mrfse_0.4.2.zip(r-4.5)
mrfse_0.4.2.tgz(r-4.6-x86_64)mrfse_0.4.2.tgz(r-4.6-arm64)mrfse_0.4.2.tgz(r-4.5-x86_64)mrfse_0.4.2.tgz(r-4.5-arm64)
mrfse_0.4.2.tar.gz(r-4.7-arm64)mrfse_0.4.2.tar.gz(r-4.7-x86_64)mrfse_0.4.2.tar.gz(r-4.6-arm64)mrfse_0.4.2.tar.gz(r-4.6-x86_64)
mrfse_0.4.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
mrfse/json (API)

# Install 'mrfse' in R:
install.packages('mrfse', repos = c('https://rodrigorsdc.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cppopenmp

1.78 score 12 scripts 225 downloads 11 exports 6 dependencies

Last updated from:19b4db5d34. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK121
linux-devel-x86_64OK113
source / vignettesOK204
linux-release-arm64OK116
linux-release-x86_64OK114
macos-release-arm64OK242
macos-release-x86_64OK238
macos-oldrel-arm64OK221
macos-oldrel-x86_64OK268
windows-develOK109
windows-releaseOK117
windows-oldrelOK104
wasm-releaseOK109

Exports:mrfse.cimrfse.ci.conmrfse.ci.nconmrfse.create.samplermrfse.exactmrfse.exact.conmrfse.exact.nconmrfse.samrfse.sa.conmrfse.sa.nconmrfse.sample

Dependencies:gtoolsRcppRcppArmadilloRcppParallelRfastzigg