The geometry of Gaussian double Markovian distributions
arXiv:2107.00134 · doi:10.1111/sjos.12604
Abstract
Gaussian double Markovian models consist of covariance matrices constrained by a pair of graphs specifying zeros simultaneously in the covariance 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.
33 pages, 1 figure. v4: added missing cases in Proposition 3.31