Package: mrfse 0.4.2
Rodrigo Carvalho
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:
mrfse_0.4.2.tar.gz
mrfse_0.4.2.tar.gz(r-4.5-noble)mrfse_0.4.2.tar.gz(r-4.4-noble)
mrfse_0.4.2.tgz(r-4.4-emscripten)mrfse_0.4.2.tgz(r-4.3-emscripten)
mrfse.pdf |mrfse.html✨
mrfse/json (API)
| # Install 'mrfse' in R: |
| install.packages('mrfse', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 days agofrom:19b4db5d34. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 22 2024 |
| R-4.5-linux-x86_64 | OK | Oct 22 2024 |
Exports:mrfse.cimrfse.ci.conmrfse.ci.nconmrfse.create.samplermrfse.exactmrfse.exact.conmrfse.exact.nconmrfse.samrfse.sa.conmrfse.sa.nconmrfse.sample
Dependencies:gtoolsRcppRcppArmadilloRcppGSLRcppParallelRcppZigguratRfast
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bresler's non-binary Markov random field structure estimator | mrfse.ci |
| Conservative approach for Bresler's non-binary estimator | mrfse.ci.con |
| Non-conservative approach for Bresler's non-binary estimator | mrfse.ci.ncon |
| Create a sampler for Markov random field. | mrfse.create.sampler |
| A Markov random field structure estimator | mrfse.exact |
| Conservative approach for Frondana's mrfse | mrfse.exact.con |
| Non-conservative approach for Frondana's mrfse | mrfse.exact.ncon |
| A Markov random field structure estimator using simulated annealing approach | mrfse.sa |
| Cnservative approach for Frondana's mrfse using simulated annealing | mrfse.sa.con |
| Non-conservative approach for Frondana's mrfse using simulated annealing | mrfse.sa.ncon |
| Generate a independent sample of a Markov random field | mrfse.sample |
