Maximum likelihood fitting of acyclic directed mixed graphs to binary data

Details Maximum likelihood fitting of acyclic directed mixed graphs to binary data Maximum likelihood fitting of acyclic directed mixed graphs to binary data

2012-03-15

arxiv.org/abs/1203.3479v1

Statistics

Methodology

Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010)

Scientific paper

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.

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