Package: bnlearn
Type: Package
Title: Bayesian network structure learning, parameter learning and
        inference
Version: 3.4
Date: 2013-07-26
Depends: R (>= 2.13.2), methods
Suggests: snow, graph, Rgraphviz, lattice, gRain
Author: Marco Scutari
Maintainer: Marco Scutari <marco.scutari@gmail.com>
Description: Bayesian network structure learning (via constraint-based, score-based and
  hybrid algorithms), parameter learning (via ML and Bayesian estimators) and 
  inference. 
  This package implements the Grow-Shrink (GS) algorithm, the Incremental Association
  (IAMB) algorithm, the Interleaved-IAMB (Inter-IAMB) algorithm, the Fast-IAMB
  (Fast-IAMB) algorithm, the Max-Min Parents and Children (MMPC) algorithm, the Hiton-PC
  algorithm, the ARACNE and Chow-Liu algorithms, the Hill-Climbing (HC) greedy search
  algorithm, the Tabu Search (TABU) algorithm, the Max-Min Hill-Climbing (MMHC) 
  algorithm and the two-stage Restricted Maximization (RSMAX2) algorithm for both discrete
  and 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 and inference, conditional probability queries and cross-validation.
URL: http://www.bnlearn.com/
License: GPL (>= 2)
LazyLoad: yes
LazyData: yes
Packaged: 2013-07-26 20:32:56 UTC; fizban
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2013-07-26 22:47:16
