Maximum Likelihood Fitting of Acyclic Directed Mixed Graphs to Binary Data
Abstract
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. In this paper we present the first method for fitting these models to binary data using maximum likelihood estimation.
Cite
Text
Evans and Richardson. "Maximum Likelihood Fitting of Acyclic Directed Mixed Graphs to Binary Data." Conference on Uncertainty in Artificial Intelligence, 2010.Markdown
[Evans and Richardson. "Maximum Likelihood Fitting of Acyclic Directed Mixed Graphs to Binary Data." Conference on Uncertainty in Artificial Intelligence, 2010.](https://mlanthology.org/uai/2010/evans2010uai-maximum/)BibTeX
@inproceedings{evans2010uai-maximum,
title = {{Maximum Likelihood Fitting of Acyclic Directed Mixed Graphs to Binary Data}},
author = {Evans, Robin J. and Richardson, Thomas S.},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2010},
pages = {177-184},
url = {https://mlanthology.org/uai/2010/evans2010uai-maximum/}
}