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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
Version
0.9-6
0.9-5
0.9-4
0.9-3
0.9-2
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)
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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