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Research code related Square Root Graphical Models (SQR) and related Poisson review paper.
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Please cite one or more of the following relevant papers if you use this code.

Code for Square Root Graphical Model (SQR) is based on:

David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon. Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies International Conference on Machine Learning (ICML), 2016.

Code and data are also provided for the following review paper.

David I. Inouye, Eunho Yang, Genevera I. Allen, Pradeep Ravikumar.
A review of multivariate distributions for count data derived from the Poisson distribution.
Wiley Interdisciplinary Reviews (WIREs): Computational Statistics, 9:3, 2017. doi: 10.1002/wics.1398
arXiv preprint:

The implementation of Square Root Graphical Models for the Poisson distribution is based on the following arXiv paper:

David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon Generalized Root Models: Beyond Pairwise Graphical Models for Univariate Exponential Families arXiv preprint arXiv:1606.00813, 2016.
arXiv preprint:


You must install the R packages VineCopula and XMRF for the vine copula and TPGM models to work respectively.


The main demo file is demo_comparison.m but the demo_comparison_check.m file checks that all the methods run to completion for a really small dataset.


The 6 datasets used in the paper are included as simple MAT files in the data folder.

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