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deal (version 1.2-4)
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
550
Version
1.2-4
License
GPL version 2 or newer
Maintainer
Claus Dethlefsen
Last Published
November 9th, 2022
Functions in deal (1.2-4)
Search all functions
elementin
Is a network element in a list of networks?
numbermixed
The number of possible networks
genlatex
From a network family, generate LaTeX output
insert
Insert/remove an arrow in network
jointprior
Calculates the joint prior distribution
line
Prints a line of symbols
learn
Estimation of parameters in the local probability distributions
addrandomarrow
Adding/Turning/Removing random arrows
addarrows
Add arrows to/from node
findex
Translation between indices in a multiway array
maketrylist
Creates the full trylist
addarrow
Adding/Turning/Removing arrows
autosearch
Greedy search
drawnetwork
Graphical interface for editing networks
makesimprob
Make a suggestion for simulation probabilities
nwfsort
Sorts a list of networks
localmaster
Local master
postdist
Calculate point estimate of posterior parameters and create probability distribution
perturb
Perturbs a network
post
Calculation of parameter posteriors for continuous node
nwequal
Test if the graphs of two networks are equal
unique.networkfamily
Makes a network family unique.
readnet
Reads/saves .net file
simulation
Simulation of data sets with a given dependency structure
node
Representation of nodes
cycletest
Test if network contains a cycle
conditional
Calculate conditional distribution
networkfamily
Generates and learns all networks for a set of variables.
network
Bayesian network data structure
rats
Weightloss of rats
ksl
Health and social characteristics