Provides a nonparametric method for estimating scale-free graphical models. To avoid the usual Gaussian assumption, we restrict the graph to be a forest and build on the work of forest density estimation. The method is motivated from a Bayesian perspective and is equivalent to finding the maximum spanning tree of a weighted graph with a log degree penalty. We solve the optimization problem via a minorize-maximization procedure with Kruskal's algorithm.
|Author||Zhe Liu <[email protected]>|
|Maintainer||Zhe Liu <[email protected]u>|
|Package repository||View on GitHub|
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