Markov Equivalences for Subclasses of Loopless Mixed Graphs

10/20/2011
by   Kayvan Sadeghi, et al.
0

In this paper we discuss four problems regarding Markov equivalences for subclasses of loopless mixed graphs. We classify these four problems as finding conditions for internal Markov equivalence, which is Markov equivalence within a subclass, for external Markov equivalence, which is Markov equivalence between subclasses, for representational Markov equivalence, which is the possibility of a graph from a subclass being Markov equivalent to a graph from another subclass, and finding algorithms to generate a graph from a certain subclass that is Markov equivalent to a given graph. We particularly focus on the class of maximal ancestral graphs and its subclasses, namely regression graphs, bidirected graphs, undirected graphs, and directed acyclic graphs, and present novel results for representational Markov equivalence and algorithms.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/12/2012

Markov Equivalence Classes for Maximal Ancestral Graphs

Ancestral graphs are a class of graphs that encode conditional independe...
research
11/22/2019

Interventional Markov Equivalence for Mixed Graph Models

We study the problem of characterizing Markov equivalence of graphical m...
research
01/28/2023

Efficient Enumeration of Markov Equivalent DAGs

Enumerating the directed acyclic graphs (DAGs) of a Markov equivalence c...
research
07/05/2020

Faster algorithms for Markov equivalence

Maximal ancestral graphs (MAGs) have many desirable properties; in parti...
research
03/09/2023

Characterizing bearing equivalence in directed graphs

In this paper, we study bearing equivalence in directed graphs. We first...
research
08/22/2022

Towards standard imsets for maximal ancestral graphs

The imsets of <cit.> are an algebraic method for representing conditiona...
research
11/06/2020

Efficient Permutation Discovery in Causal DAGs

The problem of learning a directed acyclic graph (DAG) up to Markov equi...

Please sign up or login with your details

Forgot password? Click here to reset