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sparsebnUtils

A set of tools for representing and estimating sparse Bayesian networks from continuous and discrete data.

Overview

This package provides various S3 classes for making it easy to estimate graphical models from data:

  • sparsebnData for managing experimental data with interventions.
  • sparsebnFit for representing the output of a DAG learning algorithm.
  • sparsebnPath for representing a solution path of estimates.

The package also provides methods for manipulating these objects and for estimating parameters in graphical models:

  • estimate.parameters for directed graphs.
  • get.precision for undirected graphs.
  • get.covariance for covariance matrices.

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Install

install.packages('sparsebnUtils')

Monthly Downloads

59

Version

0.0.8

License

GPL (>= 2)

Issues

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Maintainer

Bryon Aragam

Last Published

January 27th, 2021

Functions in sparsebnUtils (0.0.8)

degrees

Degree distribution of a graph
count.interventions

Count the number of rows under intervention
as.data.frame.sparsebnData

Convert a sparsebnData object back to a data.frame
fit_glm_dag

Inference in Bayesian networks
estimate.parameters

Estimate the parameters of a Bayesian network
as.sparse

as.sparse
count.levels

Count the number of levels per variable
edgeList

edgeList class
coerce_discrete

Recode discrete data
as.edgeList

as.edgeList
is.zero.edgeList

is.zero
num.samples

num.samples
get.adjacency.matrix.edgeList

get.adjacency.matrix
get.covariance

Covariance and precision matrices
num.nodes.edgeList

num.nodes
get.solution

Select solutions from a solution path
openCytoscape

Display graphs in Cytoscape
is.obs

Check if data is observational
permute.nodes

Permute the order of nodes in a graph
sparsebnData

sparsebnData class
sparsebn-messages

Messages
fit_multinom_dag

Inference in discrete Bayesian networks
show.parents

Inspect subgraph
plot.edgeList

Plot a fitted Bayesian network object
num.edges.edgeList

num.edges
sparse

sparse class
sparsebnFit

sparsebnFit class
random.dag

Generate random DAGs
sparsebnPath

sparsebnPath class
random.spd

Generate a random positive definite matrix
random.graph

Generate random DAGs
get.lambdas

get.lambdas
select

Select solutions from a solution path
select.parameter

Tuning parameter selection
get.nodes

get.nodes
generate.lambdas

generate.lambdas
to_bn

Conversion between graph types
to_edgeList

Conversion to edgeList object
pick_family

Utility functions
setPlotPackage

Change default plotting mechanism
resetGraphPackage

Change data structure for representing graphs internally
sparsebnUtils

sparsebnUtils: Utilities for the sparsebn package.
specify.prior

Build a black list based on prior knowledge