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mrfse
View on CRAN: Click
here
Download and install mrfse package within the R console
Install from CRAN:
install.packages("mrfse")
Install from Github:
library("remotes")
install_github("cran/mrfse")
Install by package version:
library("remotes")
install_version("mrfse", "0.4.2")
Attach the package and use:
library("mrfse")
Maintained by
Rodrigo Carvalho
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-08
Latest Update: 2022-11-16
Description:
Some associated R codes: RcppExports.R . bayes_sample.R . main.R . Full mrfse package functions and examples
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) .The third one is a greedy algorithm, described in Bresler (2015)
How to cite:
Rodrigo Carvalho (2019). mrfse: Markov Random Field Structure Estimator. R package version 0.4.2, https://cran.r-project.org/web/packages/mrfse. Accessed 31 Mar. 2025.
Previous versions and publish date:
Other packages that cited mrfse R package
View mrfse citation profile
Other R packages that mrfse depends,
imports, suggests or enhances
Complete documentation for mrfse
Functions, R codes and Examples using
the mrfse R package
Some associated functions: mrfse . mrfse_bresler . mrfse_bresler_con . mrfse_bresler_ncon . mrfse_con . mrfse_create_sampler . mrfse_ncon . mrfse_sa . mrfse_sa_con . mrfse_sa_ncon . mrfse_sample .
Some associated R codes: RcppExports.R . bayes_sample.R . main.R . Full mrfse package functions and examples
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