Handling Linear Gaussian Bayesian Networks
Arc matrix from an adjacency matrix
creates a crossed-adjacency matrix from two ones
standardized /nbn/ from an adjacency matrix
adjacency matrix of a /nbn/
Adjacency matrices of DAGs having three nodes
returns the number(s) of arcs of a /nbn/
returns the list of 'parallel' arcs of a crossed-nbn
transforms a /bn/ of /bnlearn/ package to a /nbn/
transforms a /bn.fit/ of /bnlearn/ package to a /nbn/
computes the correlation matrix of a chain
transforms a /chain/ to a /gema/
computes the distribution of a chain
transforms a /chain/ to a /nbn/
computes the precision of a chain
extracts a chain from a chain
checks a /chain/ object
checks a /gema/ object
checks a /nbn/ object
computes some conditional distribution of a multinormal vector
returns the correlation matrix from the variance
creates a crossed-nbn from two /nbn/s
Computes the deviance for a sample of multinormal vector
returns a score of the difference between two /nbn/s
estimates the parameters of a nbn with equality constraints
estimating the /nbn/ parameters
computes a /mn/ from a /gema/
computes a /nbn/ from a /gema/
generation of a /chain/ /nbn/
returns a randomly built /nbn/ object.
reduces a chain to its inputs and outputs
Checks if a given /nbn/ is a /chain/
returns marginal expectations and standard deviations of a chain
computes a /gema/ from a /mn/
computes a joint distribution from a marginal and a conditional one fo...
number of Bayesian networks
transforms a /nbn/ to a /bn.fit/ of /bnlearn/ package
transforms a /nbn/ into a /chain/
computes a /gema/ from a /nbn/
computes the joint distribution of a /nbn/
computes the /nbn/ changing its topological order
computes standard matrices from a /nbn/
From a /nbn/ computes the associated nbn1
a /nbn/ from a regression matrix
normalizes a /nbn/
Some examplifying structures
returns a topological order of a /chain/ or checks a proposed order.
topological order of a /gema/
topological order of a /nbn/
prints a /chain/ object
standard print function for a /gema/ object.
standard print function for a /mn/ object.
print function for a /nbn/ object.
Linear Gaussian Bayesian network manipulations
reverses the nodes of a chain
removes somes nodes from an adjacency matrix
removes some nodes from a /nbn/
regression matrix of a /nbn/
simulates from a /gema/ object
simulates a multinormal vector with varying expectation
simulates a multinormal vector
simulates from a /nbn/ object
returns the states of each node of a chain
provides so-called string model of a /nbn/
returns the precision matrix from the variance
Creation, manipulation, simulation of linear Gaussian Bayesian networks from text files and more...