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deal (version 1.2-35)
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
629
Version
1.2-35
License
GPL (>= 2)
Maintainer
Claus Dethlefsen
Last Published
August 14th, 2012
Functions in deal (1.2-35)
Search functions
node
Representation of nodes
insert
Insert/remove an arrow in network
rnetwork
Simulation of data sets with a given dependency structure
learn
Estimation of parameters in the local probability distributions
autosearch
Greedy search
prob
Local probability distributions
readnet
Reads/saves .net file
jointprior
Calculates the joint prior distribution
drawnetwork
Graphical interface for editing networks
score
Network score
networkfamily
Generates and learns all networks for a set of variables.
unique.networkfamily
Makes a network family unique.
Network tools
Tools for manipulating networks
numbermixed
The number of possible networks
nwfsort
Sorts a list of networks
network
Bayesian network data structure
perturb
Perturbs a network
maketrylist
Creates the full trylist
deal-internal
deal internal functions
makesimprob
Make a suggestion for simulation probabilities
genlatex
From a network family, generate LaTeX output
rats
Weightloss of rats
ksl
Health and social characteristics