bnstruct
R package bnstruct: 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.
Keywords for this software
References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
Sorted by year (- Polina Suter, Jack Kuipers, Giusi Moffa, Niko Beerenwinkel: Bayesian structure learning and sampling of Bayesian networks with the R package BiDAG (2021) arXiv
- Julien Chiquet, Pierre Barbillon, Timothée Tabouy: missSBM: An R Package for Handling Missing Values in the Stochastic Block Model (2019) arXiv
- Sanguinetti, Guido (ed.); Huynh-Thu, Vân Anh (ed.): Gene regulatory networks. Methods and protocols (2019)
- Kallah-Dagadu, G.; Nkansah, B. K.; Howard, N.: Probabilistic graphical modelling of causal effects among the occurrences of transcription factors in DNA sequence (2018)