Package: bgms 0.1.3.1

bgms: Bayesian Analysis of Networks of Binary and/or Ordinal Variables

Bayesian variable selection methods for analyzing the structure of a Markov Random Field model for a network of binary and/or ordinal variables. Details of the implemented methods can be found in: Marsman and Haslbeck (2023) <doi:10.31234/osf.io/ukwrf>.

Authors:Maarten Marsman [aut, cre], Karoline Huth [ctb], Nikola Sekulovski [ctb], Don van den Bergh [ctb]

bgms_0.1.3.1.tar.gz
bgms_0.1.3.1.zip(r-4.5)bgms_0.1.3.1.zip(r-4.4)bgms_0.1.3.1.zip(r-4.3)
bgms_0.1.3.1.tgz(r-4.4-x86_64)bgms_0.1.3.1.tgz(r-4.4-arm64)bgms_0.1.3.1.tgz(r-4.3-x86_64)bgms_0.1.3.1.tgz(r-4.3-arm64)
bgms_0.1.3.1.tar.gz(r-4.5-noble)bgms_0.1.3.1.tar.gz(r-4.4-noble)
bgms_0.1.3.1.tgz(r-4.4-emscripten)bgms_0.1.3.1.tgz(r-4.3-emscripten)
bgms.pdf |bgms.html
bgms/json (API)
NEWS

# Install 'bgms' in R:
install.packages('bgms', repos = c('https://maartenmarsman.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/maartenmarsman/bgms/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • Wenchuan - Post-traumatic stress disorder symptoms of Wenchuan earthquake survivors

On CRAN:

7 exports 3 stars 2.26 score 4 dependencies 1 dependents 30 scripts 982 downloads

Last updated 8 days agofrom:72d68410bb. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 10 2024
R-4.5-win-x86_64OKSep 10 2024
R-4.5-linux-x86_64OKSep 10 2024
R-4.4-win-x86_64OKSep 10 2024
R-4.4-mac-x86_64OKSep 10 2024
R-4.4-mac-aarch64OKSep 10 2024
R-4.3-win-x86_64OKSep 10 2024
R-4.3-mac-x86_64OKSep 10 2024
R-4.3-mac-aarch64OKSep 10 2024

Exports:bgmextract_argumentsextract_edge_indicatorsextract_edge_priorsextract_pairwise_thresholdsextract_posterior_inclusion_probabilitiesmrfSampler

Dependencies:rbibutilsRcppRcppProgressRdpack

Introducing bgms

Rendered fromintroduction.Rmdusingknitr::rmarkdownon Sep 10 2024.

Last update: 2024-02-09
Started: 2023-04-13