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BoltzMM  

Boltzmann Machines with MM Algorithms
View on CRAN: Click here


Download and install BoltzMM package within the R console
Install from CRAN:
install.packages("BoltzMM")

Install from Github:
library("remotes")
install_github("cran/BoltzMM")

Install by package version:
library("remotes")
install_version("BoltzMM", "0.1.4")



Attach the package and use:
library("BoltzMM")
Maintained by
Andrew Thomas Jones
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-03-19
Latest Update: 2019-02-14
Description:
Provides probability computation, data generation, and model estimation for fully-visible Boltzmann machines. It follows the methods described in Nguyen and Wood (2016a) and Nguyen and Wood (2016b) .
How to cite:
Andrew Thomas Jones (2018). BoltzMM: Boltzmann Machines with MM Algorithms. R package version 0.1.4, https://cran.r-project.org/web/packages/BoltzMM. Accessed 31 Jan. 2025.
Previous versions and publish date:
0.1.0 (2018-03-19 15:55), 0.1.1 (2018-03-26 08:31), 0.1.3 (2019-01-10 08:40)
Other packages that cited BoltzMM R package
View BoltzMM citation profile
Other R packages that BoltzMM depends, imports, suggests or enhances
Complete documentation for BoltzMM
Functions, R codes and Examples using the BoltzMM R package
Some associated functions: BoltzMM . allpfvbm . fitfvbm . fvbmHess . fvbmcov . fvbmpartiald . fvbmstderr . fvbmtests . marginpfvbm . pfvbm . rfvbm . senate . 
Some associated R codes: BoltzMM.R . RcppExports.R .  Full BoltzMM package functions and examples
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