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Found 8 papers, 0 papers with code
A Nonparametric Bayes Approach to Online Activity Prediction
We derive closed-form expressions for the number of new users expected in a given period, and a simple Monte Carlo algorithm targeting the posterior distribution of the number of days needed to attain a desired number of users; the latter is important for experimental planning.
Assumptions and Bounds in the Instrumental Variable Model
In this note we give proofs for results relating to the Instrumental Variable (IV) model with binary response $Y$ and binary treatment $X$, but with an instrument $Z$ with $K$ states.
The m-connecting imset and factorization for ADMG models
The m-connecting imset and factorization criterion provide two new statistical tools for learning and inference with ADMG models.
Multivariate Counterfactual Systems And Causal Graphical Models
Among Judea Pearl's many contributions to Causality and Statistics, the graphical d-separation} criterion, the do-calculus and the mediation formula stand out.
Methodology 62P10
A factorization criterion for acyclic directed mixed graphs
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.
Sparse Nested Markov models with Log-linear Parameters
To make modeling and inference with nested Markov models practical, it is necessary to limit the number of parameters in the model, while still correctly capturing the constraints in the marginal of a DAG model.
Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (2006)
This is the Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence, which was held in Cambridge, MA, July 13 - 16 2006.
Learning high-dimensional directed acyclic graphs with latent and selection variables
However, we prove that any causal information in the output of RFCI is correct in the asymptotic limit.
