We provide a classification of graphical models according to their representation as exponential families. Undirected graphical models with no hidden variables are linear exponential families (LEFs), directed acyclic graphical (DAG) models and chain graphs with no hidden variables, including DAG models with several families of local distributions, are curved exponential families (CEFs) and graphical models with hidden variables are stratified exponential families (SEFs). A SEF is a finite union of CEFs of various dimensions satisfying some regularity conditions. The main results of this paper are that graphical models are SEFs and that many graphical models are not CEFs. That is, roughly speaking, graphical models when viewed as exponential...
summary:We compare alternative definitions of undirected graphical models for discrete, finite varia...
In the thesis "On Boundaries of Statistical Models" problems related to a description of probability...
The most promising class of statistical models for expressing structural properties of social networ...
Undirected graphical models, or Markov networks, are a popular class of statistical models, used in ...
Undirected graphical models, also known as Markov networks, enjoy popularity in a variety of applica...
There has been an explosion of interest in statistical models for analyzing network data, and consid...
Curved exponential family models are a useful generalization of exponential random graph models (ERG...
We propose a class of closed-form estimators for sparsity-structured graphical models, expressed as ...
Networks are being increasingly used to represent relational data. As the patterns of relations tend...
Learning the structure of a graphical model is a fundamental problem and it is used extensively to i...
Exponential-family random graph models (ERGMs) represent the processes that govern the formation of...
AbstractThe closure of a discrete exponential family is described by a finite set of equations corre...
© 2016 London Mathematical Society. Exponential varieties arise from exponential families in statist...
Gaussian graphical models represent the backbone of the statistical toolbox for analyzing continuous...
Graphical models (GMs) define a family of mathematical models aimed at the concise description of mu...
summary:We compare alternative definitions of undirected graphical models for discrete, finite varia...
In the thesis "On Boundaries of Statistical Models" problems related to a description of probability...
The most promising class of statistical models for expressing structural properties of social networ...
Undirected graphical models, or Markov networks, are a popular class of statistical models, used in ...
Undirected graphical models, also known as Markov networks, enjoy popularity in a variety of applica...
There has been an explosion of interest in statistical models for analyzing network data, and consid...
Curved exponential family models are a useful generalization of exponential random graph models (ERG...
We propose a class of closed-form estimators for sparsity-structured graphical models, expressed as ...
Networks are being increasingly used to represent relational data. As the patterns of relations tend...
Learning the structure of a graphical model is a fundamental problem and it is used extensively to i...
Exponential-family random graph models (ERGMs) represent the processes that govern the formation of...
AbstractThe closure of a discrete exponential family is described by a finite set of equations corre...
© 2016 London Mathematical Society. Exponential varieties arise from exponential families in statist...
Gaussian graphical models represent the backbone of the statistical toolbox for analyzing continuous...
Graphical models (GMs) define a family of mathematical models aimed at the concise description of mu...
summary:We compare alternative definitions of undirected graphical models for discrete, finite varia...
In the thesis "On Boundaries of Statistical Models" problems related to a description of probability...
The most promising class of statistical models for expressing structural properties of social networ...