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The geometry of Gaussian double Markovian distributions
Authors:Tobias Boege  Thomas Kahle  Andreas Kretschmer  Frank Röttger
Institution:1. Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany;2. Fakultät für Mathematik, Otto von Guericke University Magdeburg, Magdeburg, Germany;3. Research Center for Statistics, Université de Genève, Geneva, Switzerland
Abstract:Gaussian double Markovian models consist of covariance matrices constrained by a pair of graphs specifying zeros simultaneously in the matrix and its inverse. We study the semi-algebraic geometry of these models, in particular their dimension, smoothness, and connectedness as well as algebraic and combinatorial properties.
Keywords:conditional independence  Gaussian  graphical models  model geometry  normal distribution  smoothness
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