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02/08/2023
Potential Outcome and Decision Theoretic Foundations for Statistical Causality
In a recent paper published in the Journal of Causal Inference, Philip D...
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07/18/2022
The m-connecting imset and factorization for ADMG models
Directed acyclic graph (DAG) models have become widely studied and appli...
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03/03/2021
Discussion of 'Estimating time-varying causal excursion effect in mobile health with binary outcomes' by T. Qian et al
We discuss the recent paper on "excursion effect" by T. Qian et al. (202...
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08/13/2020
An Interventionist Approach to Mediation Analysis
Judea Pearl's insight that, when errors are assumed independent, the Pur...
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08/13/2020
Multivariate Counterfactual Systems And Causal Graphical Models
Among Judea Pearl's many contributions to Causality and Statistics, the ...
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07/28/2020
Estimation of local treatment under the binary instrumental variable model
Instrumental variables are widely used to deal with unmeasured confoundi...
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03/19/2020
Chernoff-type Concentration of Empirical Probabilities in Relative Entropy
We study the relative entropy of the empirical probability vector with r...
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02/07/2020
Empirical Bayes for Large-scale Randomized Experiments: a Spectral Approach
Large-scale randomized experiments, sometimes called A/B tests, are incr...
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06/05/2019
On Testing Marginal versus Conditional Independence
We consider testing marginal independence versus conditional independenc...
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06/03/2019
Multiplicative Effect Modeling: The General Case
Generalized linear models, such as logistic regression, are widely used ...
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06/26/2014
A factorization criterion for acyclic directed mixed graphs
Acyclic directed mixed graphs, also known as semi-Markov models represen...
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09/26/2013
Sparse Nested Markov models with Log-linear Parameters
Hidden variables are ubiquitous in practical data analysis, and therefor...
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02/13/2013
A Discovery Algorithm for Directed Cyclis Graphs
Directed acyclic graphs have been used fruitfully to represent causal st...
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01/10/2013
Cross-covariance modelling via DAGs with hidden variables
DAG models with hidden variables present many difficulties that are not ...
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12/12/2012
Markov Equivalence Classes for Maximal Ancestral Graphs
Ancestral graphs are a class of graphs that encode conditional independe...
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10/19/2012
A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal Independence
Graphical models with bi-directed edges (<->) represent marginal indepen...
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10/19/2012
Using the structure of d-connecting paths as a qualitative measure of the strength of dependence
Pearls concept OF a d - connecting path IS one OF the foundations OF the...
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08/25/2012
Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (2006)
This is the Proceedings of the Twenty-Second Conference on Uncertainty i...
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07/20/2012
Parameter and Structure Learning in Nested Markov Models
The constraints arising from DAG models with latent variables can be nat...
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07/11/2012
Iterative Conditional Fitting for Gaussian Ancestral Graph Models
Ancestral graph models, introduced by Richardson and Spirtes (2002), gen...
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07/04/2012
Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables
It is well known that there may be many causal explanations that are con...
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03/15/2012
Maximum likelihood fitting of acyclic directed mixed graphs to binary data
Acyclic directed mixed graphs, also known as semi-Markov models represen...
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02/14/2012
