Utilities for Learning Sparse Bayesian Networks

A set of tools for representing and estimating sparse Bayesian networks from continuous and discrete data, as described in Aragam, Gu, and Zhou (2017) .

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.