Identification of Strong Edges in AMP Chain Graphs

11/23/2017
by   Jose M. Peña, et al.
0

The essential graph is a distinguished member of a Markov equivalence class of AMP chain graphs. However, the directed edges in the essential graph are not necessarily strong or invariant, i.e. they may not be shared by every member of the equivalence class. Likewise for the undirected edges. In this paper, we develop a procedure for identifying which edges in an essential graph are strong. We also show how this makes it possible to bound some causal effects when the true chain graph is unknown.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/23/2016

Formulas for Counting the Sizes of Markov Equivalence Classes of Directed Acyclic Graphs

The sizes of Markov equivalence classes of directed acyclic graphs play ...
research
03/02/2023

Identifiability and Consistent Estimation of the Gaussian Chain Graph Model

The chain graph model admits both undirected and directed edges in one g...
research
03/09/2018

On the Properties of MVR Chain Graphs

Depending on the interpretation of the type of edges, a chain graph can ...
research
10/16/2020

Minimal enumeration of all possible total effects in a Markov equivalence class

In observational studies, when a total causal effect of interest is not ...
research
11/22/2021

Bayesian Robust Learning in Chain Graph Models for Integrative Pharmacogenomics

Integrative analysis of multi-level pharmacogenomic data for modeling de...
research
09/01/2020

Strong Hanani-Tutte for the Torus

If a graph can be drawn on the torus so that every two independent edges...
research
11/11/2018

Unifying Gaussian LWF and AMP Chain Graphs to Model Interference

An intervention may have an effect on units other than those to which th...

Please sign up or login with your details

Forgot password? Click here to reset