README.md

In zhejosephliu/blossomTree: Blossom Tree Graphical Models

blossomTree

This is blossomTree R package for blossom tree graph structure estimation and density estimation.

For more information please contact [e-mail]

Description

Blossom tree graphical models combine the ideas behind trees and Gaussian graphical models to form a new nonparametric family of graphical models. The approach is to attach nonparanormal blossoms, with arbitrary graphs, to a collection of nonparametric trees. The tree edges are chosen to connect variables that most violate joint Gaussianity. The non-tree edges are partitioned into disjoint groups, and assigned to tree nodes using a nonparametric partial correlation statistic. A nonparanormal blossom is then grown for each group using established methods based on the graphical lasso. The result is a factorization with respect to the union of the tree branches and blossoms, defining a high-dimensional joint density that can be efficiently estimated and evaluated on test points.

Installation

To install the devtools package:

install.packages("devtools")
library(devtools)
install_github("zhejosephliu/blossomTree")

Usage

Please read the documentation for the main function blossomTree.

References

Zhe Liu and John Lafferty. Blossom tree graphical models. NIPS, 2014.

zhejosephliu/blossomTree documentation built on May 4, 2019, 10:17 p.m.