tavazzie/bnstructScore: Bayesian Network Structure Learning from Data with Missing Values

Bayesian Network Structure Learning from Data with Missing Values. The package implements the Silander-Myllymaki complete search, the Max-Min Parents-and-Children, the Hill-Climbing, the Max-Min Hill-climbing heuristic searches, and the Structural Expectation-Maximization algorithm. Available scoring functions are BDeu, AIC, BIC. The package also implements methods for generating and using bootstrap samples, imputed data, inference. MODIFIED TO RETURN LEARNING SCORE

Getting started

Package details

Maintainer
LicenseGPL (>=2) | file LICENSE
Version1.0.11
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("tavazzie/bnstructScore")
tavazzie/bnstructScore documentation built on Dec. 23, 2021, 7:47 a.m.