# Sparse Nested Markov models with Log-linear Parameters

@article{Shpitser2013SparseNM, title={Sparse Nested Markov models with Log-linear Parameters}, author={Ilya Shpitser and Robin J. Evans and Thomas S. Richardson and James M. Robins}, journal={ArXiv}, year={2013}, volume={abs/1309.6863} }

Hidden variables are ubiquitous in practical data analysis, and therefore modeling marginal densities and doing inference with the resulting models is an important problem in statistics, machine learning, and causal inference. Recently, a new type of graphical model, called the nested Markov model, was developed which captures equality constraints found in marginals of directed acyclic graph (DAG) models. Some of these constraints, such as the so called `Verma constraint', strictly generalize… CONTINUE READING

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## Model selection and local geometry

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CITES BACKGROUND

## Smooth, identifiable supermodels of discrete DAG models with latent variables

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CITES METHODS

## Constraint-based causal discovery from multiple interventions over overlapping variable sets

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CITES METHODS

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