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cran

bnlearn:Bayesian Network Structure Learning, Parameter Learning and Inference

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 <https://www.bnlearn.com/>.

Maintained by Marco Scutari. Last updated 3 months ago.

openblas

57 stars 7.72 score 32 dependents

petergreen5678

gRaven:Bayes Nets: 'RHugin' Emulation with 'gRain'

Wrappers for functions in the 'gRain' package to emulate some 'RHugin' functionality, allowing the building of Bayesian networks consisting on discrete chance nodes incrementally, through adding nodes, edges and conditional probability tables, the setting of evidence, both 'hard' (boolean) or 'soft' (likelihoods), querying marginal probabilities and normalizing constants, and generating sets of high-probability configurations. Computations will typically not be so fast as they are with 'RHugin', but this package should assist users without access to 'Hugin' to use code written to use 'RHugin'.

Maintained by Peter Green. Last updated 6 months ago.

2.48 score 2 scripts 2 dependents

cran

dagR:Directed Acyclic Graphs: Analysis and Data Simulation

Draw, manipulate, and evaluate directed acyclic graphs and simulate corresponding data, as described in International Journal of Epidemiology 50(6):1772-1777.

Maintained by Lutz P Breitling. Last updated 2 years ago.

5 stars 1.70 score

faskally

rc:Helper for Fitting GMRF Models on River Networks in MGCV

A set of functions to help with the fitting of gmrf models for river networks in mgcv. The package is intended for the fitting 1st and 2nd order smoothers on river networks. The code is written as simply as possible to make is easy to see how GMRFs are constructed.

Maintained by Colin Millar. Last updated 2 years ago.

1.70 score 9 scripts

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