Package: bnlearn
Type: Package
Title: Bayesian Network Structure Learning, Parameter Learning and
        Inference
Version: 4.5
Date: 2019-08-04
Depends: R (>= 2.14.0), methods
Suggests: parallel, graph, Rgraphviz, lattice, gRain, ROCR, Rmpfr, gmp
Author: Marco Scutari [aut, cre], Robert Ness [ctb]
Maintainer: Marco Scutari <marco.scutari@gmail.com>
Description: Bayesian network structure learning, parameter learning and inference.
  This package implements constraint-based (PC, GS, IAMB, Inter-IAMB, Fast-IAMB, MMPC,
  Hiton-PC, HPC), pairwise (ARACNE and Chow-Liu), score-based (Hill-Climbing and Tabu
  Search) and hybrid (MMHC, RSMAX2, H2PC) structure learning algorithms for discrete,
  Gaussian and conditional Gaussian networks, along with many score functions and
  conditional independence tests.
  The Naive Bayes and the Tree-Augmented Naive Bayes (TAN) classifiers are also implemented.
  Some utility functions (model comparison and manipulation, random data generation, arc
  orientation testing, simple and advanced plots) are included, as well as support for
  parameter estimation (maximum likelihood and Bayesian) and inference, conditional
  probability queries, cross-validation, bootstrap and model averaging.
  Development snapshots with the latest bugfixes are available from <http://www.bnlearn.com>.
URL: http://www.bnlearn.com/
License: GPL (>= 2)
LazyData: yes
NeedsCompilation: yes
Packaged: 2019-08-04 15:20:23 UTC; fizban
Repository: CRAN
Date/Publication: 2019-08-05 04:20:02 UTC
Built: R 4.1.0; x86_64-w64-mingw32; 2020-08-03 03:47:30 UTC; windows
Archs: i386, x64
