LPGM.ord: Structure learning with Poisson models using the Or-LPGM...

In drisso/learn2count: Structure Learning for Count Data

Structure learning with Poisson models using the Or-LPGM algorithm

Description

This function estimates the adjacency matrix of a Local Poisson Graphical Model (LPGM) given a matrix of counts and topological ordering, using generalized linear models. It is a natural extension of the LPGM of Allen and Liu (2013). See Nguyen et al. (2022) for details.

Usage

LPGM.ord(X, order, alpha)

Arguments

X	the matrix of counts (n times p).
order	the topological ordering of variables (names of nodes).
alpha	the significant level of the tests.

Value

the estimated adjacency matrix of the graph.

References

Allen and Liu (2013). A local Poisson graphical model for inferring networksfrom sequencing data. IEEE Transactions on NanoBioscience, 12(3), 189–198.

Nguyen, Chiogna, Risso, Banzato (2022). Guided structure learning of DAGs for count data. arXiv:2206.09754.

drisso/learn2count documentation built on March 25, 2023, 4:21 p.m.