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rbmn (version 0.9-6)

Handling Linear Gaussian Bayesian Networks

Description

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

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Version

Install

install.packages('rbmn')

Monthly Downloads

219

Version

0.9-6

License

GPL (>= 2)

Maintainer

Marco Scutari

Last Published

June 30th, 2023

Functions in rbmn (0.9-6)

chain2mn

computes the distribution of a chain
check8nbn

checks a /nbn/ object
chain2pre

computes the precision of a chain
check8gema

checks a /gema/ object
chain2gema

transforms a /chain/ to a /gema/
chain2correlation

computes the correlation matrix of a chain
condi4joint

computes some conditional distribution of a multinormal vector
chain4chain

extracts a chain from a chain
cor4var

returns the correlation matrix from the variance
gema2mn

computes a /mn/ from a /gema/
generate8nbn

returns a randomly built /nbn/ object.
generate8chain

generation of a /chain/ /nbn/
mn4joint1condi

computes a joint distribution from a marginal and a conditional one for multinormal distributions
nbn2bnfit

transforms a /nbn/ to a /bn.fit/ of /bnlearn/ package
nbn2chain

transforms a /nbn/ into a /chain/
nbn4nbn

From a /nbn/ computes the associated nbn1
nb8bn

number of Bayesian networks
nbn4rmatrix

a /nbn/ from a regression matrix
nbn2gema

computes a /gema/ from a /nbn/
gema2nbn

computes a /nbn/ from a /gema/
simulate8gema

simulates from a /gema/ object
inout4chain

reduces a chain to its inputs and outputs
is8nbn8chain

Checks if a given /nbn/ is a /chain/
nbn2mn

computes the joint distribution of a /nbn/
dev4mn

Computes the deviance for a sample of multinormal vector
diff8nbn

returns a score of the difference between two /nbn/s
normalize8nbn

normalizes a /nbn/
provided objects

Some examplifying structures
crossed4nbn1nbn

creates a crossed-nbn from two /nbn/s
reverse8chain

reverses the nodes of a chain
marginal4chain

returns marginal expectations and standard deviations of a chain
print8chain

prints a /chain/ object
order4nbn

topological order of a /nbn/
simulate8gmn

simulates a multinormal vector with varying expectation
rm8nd4adja

removes somes nodes from an adjacency matrix
var2pre

returns the precision matrix from the variance
chain2nbn

transforms a /chain/ to a /nbn/
order4gema

topological order of a /gema/
estimate8nbn

estimating the /nbn/ parameters
print8nbn

print function for a /nbn/ object.
order4chain

returns a topological order of a /chain/ or checks a proposed order.
simulate8mn

simulates a multinormal vector
estimate8constrainednbn

estimates the parameters of a nbn with equality constraints
rbmn-package

Linear Gaussian Bayesian network manipulations
simulate8nbn

simulates from a /nbn/ object
print8gema

standard print function for a /gema/ object.
print8mn

standard print function for a /mn/ object.
mn2gema

computes a /gema/ from a /mn/
string7dag4nbn

provides so-called string model of a /nbn/
state4chain

returns the states of each node of a chain
nbn2nbn

computes the /nbn/ changing its topological order
nbn2rr

computes standard matrices from a /nbn/
rmatrix4nbn

regression matrix of a /nbn/
rm8nd4nbn

removes some nodes from a /nbn/
bnfit2nbn

transforms a /bn.fit/ of /bnlearn/ package to a /nbn/
adja2crossed

creates a crossed-adjacency matrix from two ones
adja2nbn

standardized /nbn/ from an adjacency matrix
adja4nbn

adjacency matrix of a /nbn/
arc7nb4nbn

returns the number(s) of arcs of a /nbn/
body composition

Body Composition Variables and Covariables
arcs4nbn1nbn

returns the list of 'parallel' arcs of a crossed-nbn
adja2arcs

Arc matrix from an adjacency matrix
adja4three

Adjacency matrices of DAGs having three nodes
bn2nbn

transforms a /bn/ of /bnlearn/ package to a /nbn/
check8chain

checks a /chain/ object