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Gaussian graphical models with toric vanishing ideals

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Abstract

Gaussian graphical models are semi-algebraic subsets of the cone of positive definite covariance matrices. They are widely used throughout natural sciences, computational biology and many other fields. Computing the vanishing ideal of the model gives us an implicit description of the model. In this paper, we resolve two conjectures given by Sturmfels and Uhler. In particular, we characterize those graphs for which the vanishing ideal of the Gaussian graphical model is generated in degree 1 and 2. These turn out to be the Gaussian graphical models whose ideals are toric ideals, and the resulting graphs are the 1-clique sums of complete graphs.

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References

  • DeLoera, J. A., Sturmfels, B., Thomas, R. R. (1995). Gröbner bases and triangulations of the second hypersimplex. Combinatorica, 15(3), 409–424.

    Article  MathSciNet  Google Scholar 

  • Dobra, A., Sullivant, S. (2004). A divide-and-conquer algorithm for generating Markov bases of multi-way tables. Computational Statistics, 19(3), 347–366.

    Article  MathSciNet  Google Scholar 

  • Drton, M., Massam, H., Olkin, I. (2008). Moments of minors of Wishart matrices. The Annals of Statistics, 36(5), 2261–2283.

    Article  MathSciNet  Google Scholar 

  • Drton, M., Sturmfels, B., Sullivant, S. (2007). Algebraic factor analysis: Tetrads, pentads and beyond. Probability Theory and Related Fields, 138(3–4), 463–493.

    Article  MathSciNet  Google Scholar 

  • Grayson, D. R., Stillman, M. E. (2017). Macaulay2, a software system for research in algebraic geometry. https://faculty.math.illinois.edu/Macaulay2/. Retrieved Sept 1, 2017

  • Hassett, B. (2007). Introduction to algebraic geometry. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Herzog, J., Hibi, T., Ohsugi, H. (2018). Binomial ideals. Graduate texts in mathematics, Vol. 29. Cham: Springer.

    Book  Google Scholar 

  • Hoşten, S., Sullivant, S. (2002). Gröbner bases and polyhedral geometry of reducible and cyclic models. Journal of Combinatorial Theory Series A, 100(2), 277–301.

    Article  MathSciNet  Google Scholar 

  • Jones, B., West, M. (2005). Covariance decomposition in undirected Gaussian graphical models. Biometrika, 92(4), 779–786.

    Article  MathSciNet  Google Scholar 

  • Kelley, T. (1935). Essential traits of mental life. Harvard studies in education, Vol. 26. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Koller, D., Friedman, N. (2009). Probabilistic graphical models. Adaptive computation and machine learning. Cambridge, MA: MIT Press.

    MATH  Google Scholar 

  • Lauritzen, S. L. (1996). Graphical models. Oxford statistical science series, Vol. 17. New York: Oxford University Press.

    Google Scholar 

  • Spirtes, P., Glymour, C., Scheines, R. (2000). Causation, prediction, and search. Adaptive computation and machine learning2nd ed. Cambridge, MA: MIT Press.

    MATH  Google Scholar 

  • Sturmfels, B. (1996). Gröbner bases and convex polytopes. University Lecture Series, Vol. 8. Providence, RI: American Mathematical Society.

    MATH  Google Scholar 

  • Sturmfels, B., Uhler, C. (2010). Multivariate Gaussian, semidefinite matrix completion, and convex algebraic geometry. Annals of the Institute of Statistical Mathematics, 62(4), 603–638.

    Article  MathSciNet  Google Scholar 

  • Sullivant, S. (2007). Toric fiber products. Journal of Algebra, 316(2), 560–577.

    Article  MathSciNet  Google Scholar 

  • Sullivant, S. (2008). Algebraic geometry of Gaussian Bayesian networks. Advances in Applied Mathematics, 40(4), 482–513.

    Article  MathSciNet  Google Scholar 

  • Sullivant, S. (2018). Algebraic statistics. Graduate Studies in Mathematics, Vol. 194. Providence, RI: American Mathematical Society.

    MATH  Google Scholar 

  • Sullivant, S., Talaska, K., Draisma, J. (2010). Trek separation for Gaussian graphical models. The Annals of Statistics, 38(3), 1665–1685.

    Article  MathSciNet  Google Scholar 

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Acknowledgements

Pratik Misra and Seth Sullivant were partially supportedby the US National Science Foundation (DMS 1615660).

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Misra, P., Sullivant, S. Gaussian graphical models with toric vanishing ideals. Ann Inst Stat Math 73, 757–785 (2021). https://doi.org/10.1007/s10463-020-00765-0

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  • DOI: https://doi.org/10.1007/s10463-020-00765-0

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