= Robin J. Evans
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<Robin J. Evans> studies <causal inference>, graphical models and the behavior of statistical models after hidden variables are marginalized. His work on margins of Bayesian networks characterizes algebraic restrictions that are not captured by a list of <conditional independences> alone.https://arxiv.org/abs/1501.02103[Margins of discrete Bayesian networks, author and abstract]{ref}
With <Thomas S. Richardson> and other collaborators, he coauthored <Nested Markov Properties for Acyclic Directed Mixed Graphs by Thomas S. Richardson and others>. A central idea is to describe constraints on the observed distribution without committing to an identifiable parameter for every unobserved mechanism.<Nested Markov Properties for Acyclic Directed Mixed Graphs by Thomas S. Richardson and others>[Introduction]{ref}
This matters when two models agree on ordinary independence tests yet differ in other restrictions on probabilities. Separating these cases can improve both model interpretation and estimation: a convenient parameterization of the observed model need not identify the underlying hidden causal story. His institutional personal-page redirect leads to his research-group site.https://www.stats.ox.ac.uk/~evans/[Author's institutional homepage redirect]{ref}
\Image[https://rje42.github.io/images/me.jpg]
{title=Robin J. Evans, portrait identified by the linked author, institutional or Commons source}
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