Package: rbmn 0.9-6

Marco Scutari

rbmn: Handling Linear Gaussian Bayesian Networks

Creation, manipulation, simulation of linear Gaussian Bayesian networks from text files and more...

Authors:Jean-Baptiste Denis [aut, cre], Marco Scutari [ctb]

rbmn_0.9-6.tar.gz
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rbmn.pdf |rbmn.html✨
rbmn/json (API)

# Install 'rbmn' in R:
install.packages('rbmn', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • boco - Body Composition Variables and Covariables

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

86 exports 0.00 score 1 dependencies 73 scripts 308 downloads

Last updated 1 years agofrom:c20b0b2444. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 15 2024
R-4.5-linuxOKSep 15 2024

Exports:adja2arcsadja2crossedadja2nbnadja4nbnadja4threearc7nb4nbnarcs4nbn1nbnbn2nbnbnfit2nbnchain2correlationchain2gemachain2mnchain2nbnchain2prechain4chaincheck8chaincheck8gemacheck8nbncondi4jointcor4varcrossed4nbn1nbndev4mndiff8nbnestimate8constrainednbnestimate8nbngema2mngema2nbngenerate8chaingenerate8nbninout4chainis8nbn8chainmarginal4chainmn2gemamn4joint1condinb8bnnbn2bnfitnbn2chainnbn2gemanbn2mnnbn2nbnnbn2rrnbn4nbnnbn4rmatrixnormalize8nbnorder4chainorder4gemaorder4nbnprint8chainprint8gemaprint8mnprint8nbnrbmn0adja.01rbmn0adja.02rbmn0adja.03rbmn0adja.04rbmn0adja.05rbmn0chain.01rbmn0chain.02rbmn0chain.03rbmn0crarc.05rbmn0gema.01rbmn0gema.02rbmn0gema.03rbmn0gema.04rbmn0gema.05rbmn0mn.01rbmn0mn.02rbmn0mn.03rbmn0mn.04rbmn0mn.05rbmn0nbn.01rbmn0nbn.02rbmn0nbn.03rbmn0nbn.04rbmn0nbn.05reverse8chainrm8nd4adjarm8nd4nbnrmatrix4nbnsimulate8gemasimulate8gmnsimulate8mnsimulate8nbnstate4chainstring7dag4nbnvar2pre

Dependencies:MASS

Readme and manuals

Help Manual

Help pageTopics
Linear Gaussian Bayesian network manipulationsrbmn-package rbmn
Arc matrix from an adjacency matrixadja2arcs
creates a crossed-adjacency matrix from two onesadja2crossed
standardized /nbn/ from an adjacency matrixadja2nbn
adjacency matrix of a /nbn/adja4nbn
Adjacency matrices of DAGs having three nodesadja4three
returns the number(s) of arcs of a /nbn/arc7nb4nbn
returns the list of 'parallel' arcs of a crossed-nbnarcs4nbn1nbn
transforms a /bn/ of /bnlearn/ package to a /nbn/bn2nbn
transforms a /bn.fit/ of /bnlearn/ package to a /nbn/bnfit2nbn
Body Composition Variables and Covariablesboco
computes the correlation matrix of a chainchain2correlation
transforms a /chain/ to a /gema/chain2gema
computes the distribution of a chainchain2mn
transforms a /chain/ to a /nbn/chain2nbn
computes the precision of a chainchain2pre
extracts a chain from a chainchain4chain
checks a /chain/ objectcheck8chain
checks a /gema/ objectcheck8gema
checks a /nbn/ objectcheck8nbn
computes some conditional distribution of a multinormal vectorcondi4joint
returns the correlation matrix from the variancecor4var
creates a crossed-nbn from two /nbn/scrossed4nbn1nbn
Computes the deviance for a sample of multinormal vectordev4mn
returns a score of the difference between two /nbn/sdiff8nbn
estimates the parameters of a nbn with equality constraintsestimate8constrainednbn
estimating the /nbn/ parametersestimate8nbn
computes a /mn/ from a /gema/gema2mn
computes a /nbn/ from a /gema/gema2nbn
generation of a /chain/ /nbn/generate8chain
returns a randomly built /nbn/ object.generate8nbn
reduces a chain to its inputs and outputsinout4chain
Checks if a given /nbn/ is a /chain/is8nbn8chain
returns marginal expectations and standard deviations of a chainmarginal4chain
computes a /gema/ from a /mn/mn2gema
computes a joint distribution from a marginal and a conditional one for multinormal distributionsmn4joint1condi
number of Bayesian networksnb8bn
transforms a /nbn/ to a /bn.fit/ of /bnlearn/ packagenbn2bnfit
transforms a /nbn/ into a /chain/nbn2chain
computes a /gema/ from a /nbn/nbn2gema
computes the joint distribution of a /nbn/nbn2mn
computes the /nbn/ changing its topological ordernbn2nbn
computes standard matrices from a /nbn/nbn2rr
From a /nbn/ computes the associated nbn1nbn4nbn
a /nbn/ from a regression matrixnbn4rmatrix
normalizes a /nbn/normalize8nbn
returns a topological order of a /chain/ or checks a proposed order.order4chain
topological order of a /gema/order4gema
topological order of a /nbn/order4nbn
prints a /chain/ objectprint8chain
standard print function for a /gema/ object.print8gema
standard print function for a /mn/ object.print8mn
print function for a /nbn/ object.print8nbn
Some examplifying structuresprovided objects rbmn0adja.01 rbmn0adja.02 rbmn0adja.03 rbmn0adja.04 rbmn0adja.05 rbmn0chain.01 rbmn0chain.02 rbmn0chain.03 rbmn0crarc.05 rbmn0gema.01 rbmn0gema.02 rbmn0gema.03 rbmn0gema.04 rbmn0gema.05 rbmn0mn.01 rbmn0mn.02 rbmn0mn.03 rbmn0mn.04 rbmn0mn.05 rbmn0nbn.01 rbmn0nbn.02 rbmn0nbn.03 rbmn0nbn.04 rbmn0nbn.05
reverses the nodes of a chainreverse8chain
removes somes nodes from an adjacency matrixrm8nd4adja
removes some nodes from a /nbn/rm8nd4nbn
regression matrix of a /nbn/rmatrix4nbn
simulates from a /gema/ objectsimulate8gema
simulates a multinormal vector with varying expectationsimulate8gmn
simulates a multinormal vectorsimulate8mn
simulates from a /nbn/ objectsimulate8nbn
returns the states of each node of a chainstate4chain
provides so-called string model of a /nbn/string7dag4nbn
returns the precision matrix from the variancevar2pre