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Discrete Graphical Models and Their Parameterization
2018This chapter is devoted to graphical models in which the observed variables are categorical, that is, whose state space consists of a finite number of values. The focus is on regression graph models, because this family of models allows us to approach discrete graphical models with a sufficient degree of generality.
La Rocca, Luca, Roverato, Alberto
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Graphical Models for Processing Missing Data
Journal of the American Statistical Association, 2021Karthika Mohan, Judea Pearl
exaly
1995
Abstract The aim of this chapter is to provide a non-technical overview of graphical modelling. Independence graphs with both lines (undirected edges) and arrows (directed edges) are described, together with associated models in duding both discrete and continuous variables. Some discussion of causal inference is also given. Graphical
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Abstract The aim of this chapter is to provide a non-technical overview of graphical modelling. Independence graphs with both lines (undirected edges) and arrows (directed edges) are described, together with associated models in duding both discrete and continuous variables. Some discussion of causal inference is also given. Graphical
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Review of Causal Discovery Methods Based on Graphical Models
Frontiers in Genetics, 2019Kun Zhang +2 more
exaly
High-dimensional semiparametric Gaussian copula graphical models
Annals of Statistics, 2012Ming Yuan, Larry Wasserman, Fang Han
exaly
Graphical Network Models for International Financial Flows
Journal of Business and Economic Statistics, 2016Paolo Stefano Giudici
exaly
Dynamic graphical models of molecular kinetics
Proceedings of the National Academy of Sciences of the United States of America, 2019Simon Olsson, Frank Noe, Noe Frank
exaly
Graphical models for imprecise probabilities
International Journal of Approximate Reasoning, 2005Fabio Gagliardi Cozman
exaly

