rbmn-package: Linear Gaussian Bayesian network manipulations

Description Details Projected evolution of /mn/ TO DO list Author(s) References Examples

Description

General functions to generate, transform, display general and particular linear Gaussian Bayesian networks [/nbn/] are provided.
Specific /nbn/ are chain and crossed /nbn/s. Focus is given in getting joint and conditional probability distributions of the set of nodes.
rbmn stands for R'eseau Bay'esien MultiNormal.

Details

Some basic concepts:

Three equivalent ways can be used to represent the joint probability distribution of a set of nodes respectively associated to the structures /mn/, /nbn/ and /gema/:

To relieve the memory effort, most names of the functions have been given a two (or more) components structure separated with a figure. This idea will be explained and exploited in a package to come named documair. The approximate meaning of the figures are:

A number of ancillary functions have not been exported to give a better access to the main function of /rbmn/. Nevertheless they are available in the ../rbmn/R/ directory, and with all their comments (equivalent to Rd files into ../rbmn/inst/original/ directory). Some of them are visible when defining the default arguments of some functions.

Projected evolution of /mn/

TO DO list

Author(s)

Jean-Baptiste Denis
MIAj - Inra - Jouy-en-Josas
F-78532 Jouy-en-Josas

Maintainer: Jean-Baptiste Denis Jean-Baptiste.Denis@Jouy.Inra.Fr

References

(A technical report presenting the concepts used in rbmn is under redaction; it can be obtained as it is if asked.)

Scutari M (2010). "Learning Bayesian Networks with the bnlearn R Package". Journal of Statistical Software, 35(3), 1-22. URL http://www.jstatsoft.org/v35/i03/.

Tian S, Scutari M & Denis J-B (2013, submitted to JSFdS). "Predicting with Crossed Linear Gaussian Bayesian Networks".

Examples

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library(rbmn)

## getting the data set
data(boco)
print(head(boco));

rbmn documentation built on May 19, 2017, 2:28 p.m.

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