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deal (version 1.2-37)
Learning Bayesian Networks with Mixed Variables
Description
Bayesian networks with continuous and/or discrete variables can be learned and compared from data.
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Install
install.packages('deal')
Monthly Downloads
286
Version
1.2-37
License
GPL (>= 2)
Maintainer
Claus Dethlefsen
Last Published
January 28th, 2013
Functions in deal (1.2-37)
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drawnetwork
Graphical interface for editing networks
rnetwork
Simulation of data sets with a given dependency structure
networkfamily
Generates and learns all networks for a set of variables.
genlatex
From a network family, generate LaTeX output
makesimprob
Make a suggestion for simulation probabilities
node
Representation of nodes
Network tools
Tools for manipulating networks
nwfsort
Sorts a list of networks
readnet
Reads/saves .net file
score
Network score
unique.networkfamily
Makes a network family unique.
perturb
Perturbs a network
autosearch
Greedy search
learn
Estimation of parameters in the local probability distributions
maketrylist
Creates the full trylist
network
Bayesian network data structure
insert
Insert/remove an arrow in network
numbermixed
The number of possible networks
deal-internal
deal internal functions
jointprior
Calculates the joint prior distribution
prob
Local probability distributions
rats
Weightloss of rats
ksl
Health and social characteristics