Package: BoltzMM 0.1.4

BoltzMM: Boltzmann Machines with MM Algorithms

Provides probability computation, data generation, and model estimation for fully-visible Boltzmann machines. It follows the methods described in Nguyen and Wood (2016a) <doi:10.1162/NECO_a_00813> and Nguyen and Wood (2016b) <doi:10.1109/TNNLS.2015.2425898>.

Authors:Andrew Thomas Jones, Hien Duy Nguyen, and Jessica Juanita Bagnall

BoltzMM_0.1.4.tar.gz
BoltzMM_0.1.4.zip(r-4.5)BoltzMM_0.1.4.zip(r-4.4)BoltzMM_0.1.4.zip(r-4.3)
BoltzMM_0.1.4.tgz(r-4.4-x86_64)BoltzMM_0.1.4.tgz(r-4.4-arm64)BoltzMM_0.1.4.tgz(r-4.3-x86_64)BoltzMM_0.1.4.tgz(r-4.3-arm64)
BoltzMM_0.1.4.tar.gz(r-4.5-noble)BoltzMM_0.1.4.tar.gz(r-4.4-noble)
BoltzMM_0.1.4.tgz(r-4.4-emscripten)BoltzMM_0.1.4.tgz(r-4.3-emscripten)
BoltzMM.pdf |BoltzMM.html✨
BoltzMM/json (API)

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

Peer review:

Bug tracker:https://github.com/andrewthomasjones/boltzmm/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • senate - Senate voting data from the 45th Australian Parliament.

On CRAN:

11 exports 1 stars 0.84 score 3 dependencies 17 scripts 212 downloads

Last updated 3 years agofrom:0d07f07286. Checks:OK: 1 WARNING: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 05 2024
R-4.5-win-x86_64WARNINGSep 05 2024
R-4.5-linux-x86_64WARNINGSep 05 2024
R-4.4-win-x86_64WARNINGSep 05 2024
R-4.4-mac-x86_64WARNINGSep 05 2024
R-4.4-mac-aarch64WARNINGSep 05 2024
R-4.3-win-x86_64WARNINGSep 05 2024
R-4.3-mac-x86_64WARNINGSep 05 2024
R-4.3-mac-aarch64WARNINGSep 05 2024

Exports:allpfvbmfitfvbmfvbmcovfvbmHessfvbmpartialdfvbmstderrfvbmtestslog_pl_calcmarginpfvbmpfvbmrfvbm

Dependencies:BHRcppRcppArmadillo