summary:The simultaneous occurrence of conditional independences among subvectors of a regular Gaussian vector is examined. All configurations of the conditional independences within four jointly regular Gaussian variables are found and completely characterized in terms of implications involving conditional independence statements. The statements induced by the separation in any simple graph are shown to correspond to such a configuration within a regular Gaussian vector
Gaussian double Markovian models consist of covariance matrices constrained by a pair of graphs spec...
Gaussian graphical models are semi-algebraic subsets of the cone of positive definite covariance mat...
Conditional independence almost everywhere in the space of the conditioning variates does not imply ...
summary:The simultaneous occurrence of conditional independences among subvectors of a regular Gauss...
Summary. An independence model (a list of conditional independence statements) is said to be Gaussia...
Abstract. Conditional independence in a multivariate normal (or Gaussian) distribution is characteri...
AbstractWe show that there can be no finite list of conditional independence relations which can be ...
In this paper we study conditional independence structures arising from conditional probabilities an...
. Special conditional independence structures have been recognized to be matroids. This opens new po...
Seth Sullivant was partially supported by the David and Lucille Packard Foundation and the US Nation...
summary:An overview is given of results achieved by F. Matúš on probabilistic conditional independen...
Selfadhesivity is a property of entropic polymatroids which guarantees that the polymatroid can be g...
We explore the conditional probabilistic independences of systems of random variables (I ; J jK), to...
summary:In this paper, we characterise and classify a list of full conditional independences via the...
AbstractDifferent conditional independence models have been proposed in literature; in this paper we...
Gaussian double Markovian models consist of covariance matrices constrained by a pair of graphs spec...
Gaussian graphical models are semi-algebraic subsets of the cone of positive definite covariance mat...
Conditional independence almost everywhere in the space of the conditioning variates does not imply ...
summary:The simultaneous occurrence of conditional independences among subvectors of a regular Gauss...
Summary. An independence model (a list of conditional independence statements) is said to be Gaussia...
Abstract. Conditional independence in a multivariate normal (or Gaussian) distribution is characteri...
AbstractWe show that there can be no finite list of conditional independence relations which can be ...
In this paper we study conditional independence structures arising from conditional probabilities an...
. Special conditional independence structures have been recognized to be matroids. This opens new po...
Seth Sullivant was partially supported by the David and Lucille Packard Foundation and the US Nation...
summary:An overview is given of results achieved by F. Matúš on probabilistic conditional independen...
Selfadhesivity is a property of entropic polymatroids which guarantees that the polymatroid can be g...
We explore the conditional probabilistic independences of systems of random variables (I ; J jK), to...
summary:In this paper, we characterise and classify a list of full conditional independences via the...
AbstractDifferent conditional independence models have been proposed in literature; in this paper we...
Gaussian double Markovian models consist of covariance matrices constrained by a pair of graphs spec...
Gaussian graphical models are semi-algebraic subsets of the cone of positive definite covariance mat...
Conditional independence almost everywhere in the space of the conditioning variates does not imply ...