ccdr: ccdr: Structure learning for Bayesian networks using the CCDr...
In itsrainingdata/ccdr: CCDr Algorithm for Learning Sparse Gaussian Bayesian Networks.
Description
ccdr implements the CCDr structure learning algorithm for Bayesian networks.
Details
Based on observational data, this algorithm estimates the structure of a Bayesian network
(aka edges in a DAG) using penalized maximum likelihood based on L1 or concave (MCP) regularization.
The main methods are:
ccdr.runExecutes the main algorithm.
generate.lambdasConvenience method for generating a good sequence of regularization parameters.
itsrainingdata/ccdr documentation built on May 18, 2019, 7:12 a.m.
R Package Documentation
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Description
ccdr implements the CCDr structure learning algorithm for Bayesian networks.
Details
Based on observational data, this algorithm estimates the structure of a Bayesian network (aka edges in a DAG) using penalized maximum likelihood based on L1 or concave (MCP) regularization. The main methods are:
ccdr.runExecutes the main algorithm.
generate.lambdasConvenience method for generating a good sequence of regularization parameters.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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