In this thesis we describe subclasses of a class of graphs with three types of edges, called loopless mixed graphs (LMGs). The class of LMGs contains almost all known classes of graphs used in the literature of graphical Markov models. We focus in particular on the subclass of ribbonless graphs (RGs), which as special cases include undirected graphs, bidirected graphs, and directed acyclic graphs, as well as ancestral graphs and summary graphs. We define a unifying interpretation of independence structure for LMGs and pairwise and global Markov properties for RGs, discuss their maximality, and, in particular, prove the equivalence of pairwise and global Markov properties for graphoids defined over the nodes of RGs. Three subclasses of LMGs ...
We investigate probabilistic graphical models that allow for both cycles and latent variables. For t...
In this paper we study conditional independence structures arising from conditional probabilities an...
We present a new family of models that is based on graphs that may have undirected, directed and bid...
In this thesis we describe subclasses of a class of graphs with three types of edges, called looples...
In this thesis we describe subclasses of a class of graphs with three types of edges, called looples...
In this paper, we unify the Markov theory of a variety of different types of graphs used in graphica...
Several types of graphs with different conditional independence interpretations—also known as Markov...
This paper introduces a class of graphical independence models that is closed under marginalization ...
Conditional independence models associated with directed acyclic graphs (DAGs) may be characterized ...
We describe some functions in the R package ggm to derive from a given Markov model, represented by ...
We describe some functions in the R package ggm to derive from a given Markov model, represented by ...
AbstractIn this paper we study the problem of representing probabilistic independence models, in par...
In this paper we consider conditional independence models closed under graphoid properties. We inves...
We describe some functions in the R package ggm to derive from a given Markov model, represented by ...
Ancestral graphs can encode conditional independence relations that arise in directed acyclic graph ...
We investigate probabilistic graphical models that allow for both cycles and latent variables. For t...
In this paper we study conditional independence structures arising from conditional probabilities an...
We present a new family of models that is based on graphs that may have undirected, directed and bid...
In this thesis we describe subclasses of a class of graphs with three types of edges, called looples...
In this thesis we describe subclasses of a class of graphs with three types of edges, called looples...
In this paper, we unify the Markov theory of a variety of different types of graphs used in graphica...
Several types of graphs with different conditional independence interpretations—also known as Markov...
This paper introduces a class of graphical independence models that is closed under marginalization ...
Conditional independence models associated with directed acyclic graphs (DAGs) may be characterized ...
We describe some functions in the R package ggm to derive from a given Markov model, represented by ...
We describe some functions in the R package ggm to derive from a given Markov model, represented by ...
AbstractIn this paper we study the problem of representing probabilistic independence models, in par...
In this paper we consider conditional independence models closed under graphoid properties. We inves...
We describe some functions in the R package ggm to derive from a given Markov model, represented by ...
Ancestral graphs can encode conditional independence relations that arise in directed acyclic graph ...
We investigate probabilistic graphical models that allow for both cycles and latent variables. For t...
In this paper we study conditional independence structures arising from conditional probabilities an...
We present a new family of models that is based on graphs that may have undirected, directed and bid...