257 citations · 1k across the 41 of their papers we have counts for
4 papers · 2 filters
A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal Independence
Mathias Drton, Thomas S. Richardson
Graphical models with bi-directed edges (<->) represent marginal independence: the absence of an edge between two vertices indicates that the corresponding variables are marginally…
Iterative Conditional Fitting for Gaussian Ancestral Graph Models
Mathias Drton, Thomas S. Richardson
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property t…
Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables
Ayesha R. Ali, Thomas S. Richardson, Peter L. Spirtes +1
It is well known that there may be many causal explanations that are consistent with a given set of data. Recent work has been done to represent the common aspects of these explana…
Maximum likelihood fitting of acyclic directed mixed graphs to binary data
Robin J. Evans, Thomas S. Richardson
Acyclic directed mixed graphs, also known as semi-Markov models represent the conditional independence structure induced on an observed margin by a DAG model with latent variables.…