An Alternative Markov Property for Chain Graphs

02/13/2013
by   Steen A. Andersson, et al.
0

Graphical Markov models use graphs, either undirected, directed, or mixed, to represent possible dependences among statistical variables. Applications of undirected graphs (UDGs) include models for spatial dependence and image analysis, while acyclic directed graphs (ADGs), which are especially convenient for statistical analysis, arise in such fields as genetics and psychometrics and as models for expert systems and Bayesian belief networks. Lauritzen, Wermuth and Frydenberg (LWF) introduced a Markov property for chain graphs, which are mixed graphs that can be used to represent simultaneously both causal and associative dependencies and which include both UDGs and ADGs as special cases. In this paper an alternative Markov property (AMP) for chain graphs is introduced, which in some ways is a more direct extension of the ADG Markov property than is the LWF property for chain graph.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/27/2011

Markov properties for mixed graphs

In this paper, we unify the Markov theory of a variety of different type...
research
10/28/2015

Priors on exchangeable directed graphs

Directed graphs occur throughout statistical modeling of networks, and e...
research
10/12/2017

V1: A Visual Query Language for Property Graphs

V1 is a declarative visual query language for schema-based property grap...
research
03/09/2018

The evolution of the global Markov property for multivariate regression graphs: differences and conflicts

Depending on the interpretation of the type of edges, a chain graph can ...
research
03/27/2013

Causal Networks: Semantics and Expressiveness

Dependency knowledge of the form "x is independent of y once z is known"...
research
04/09/2017

Mixed Graphical Models for Causal Analysis of Multi-modal Variables

Graphical causal models are an important tool for knowledge discovery be...
research
03/09/2018

The evolution of multivariate regression chain graphs

Depending on the interpretation of the type of edges, a chain graph can ...

Please sign up or login with your details

Forgot password? Click here to reset