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Related papers: Markov Equivalences for Subclasses of Loopless Mix…

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In this paper, we unify the Markov theory of a variety of different types of graphs used in graphical Markov models by introducing the class of loopless mixed graphs, and show that all independence models induced by $m$-separation on such…

Other Statistics · Statistics 2014-03-13 Kayvan Sadeghi , Steffen Lauritzen

Ancestral graphs are a class of graphs that encode conditional independence relations arising in DAG models with latent and selection variables, corresponding to marginalization and conditioning. However, for any ancestral graph, there may…

Artificial Intelligence · Computer Science 2013-01-07 Ayesha R. Ali , Thomas S. Richardson

Ancestral graphs can encode conditional independence relations that arise in directed acyclic graph (DAG) models with latent and selection variables. However, for any ancestral graph, there may be several other graphs to which it is Markov…

Statistics Theory · Mathematics 2009-08-26 R. Ayesha Ali , Thomas S. Richardson , Peter Spirtes

Symmetric independence relations are often studied using graphical representations. Ancestral graphs or acyclic directed mixed graphs with $m$-separation provide classes of symmetric graphical independence models that are closed under…

Statistics Theory · Mathematics 2020-09-14 Søren Wengel Mogensen , Niels Richard Hansen

Several types of graphs with different conditional independence interpretations --- also known as Markov properties --- have been proposed and used in graphical models. In this paper we unify these Markov properties by introducing a class…

Statistics Theory · Mathematics 2017-07-12 Steffen Lauritzen , Kayvan Sadeghi

We consider sampling and enumeration problems for Markov equivalence classes. We create and analyze a Markov chain for uniform random sampling on the DAGs inside a Markov equivalence class. Though the worst case is exponentially slow…

Probability · Mathematics 2017-08-16 Megan Bernstein , Prasad Tetali

We study the graphs generated when the formula for linking Markov triples is applied to general triples of integers. We find there are a finite number of equivalence classes of graphs, each with particular properties.

General Mathematics · Mathematics 2026-02-23 Spencer Scutt , Mark Turpin

Maximal ancestral graphs (MAGs) are used to encode conditional independence relations in DAG models with hidden variables. Different MAGs may represent the same set of conditional independences and are called Markov equivalent. This paper…

Methodology · Statistics 2012-07-09 Jin Tian

Classical graphical modeling of multivariate random vectors uses graphs to encode conditional independence. In graphical modeling of multivariate stochastic processes, graphs may encode so-called local independence analogously. If some…

Statistics Theory · Mathematics 2023-02-27 Søren Wengel Mogensen

In the hidden Markov process, there is a possibility that two different transition matrices for hidden and observed variables yield the same stochastic behavior for the observed variables. Since such two transition matrices cannot be…

Statistics Theory · Mathematics 2024-09-10 Masahito Hayashi

Different directed acyclic graphs (DAGs) may be Markov equivalent in the sense that they entail the same conditional independence relations among the observed variables. Meek (1995) characterizes Markov equivalence classes for DAGs (with no…

Methodology · Statistics 2012-06-26 Jiji Zhang

Maximal ancestral graphs (MAGs) have many desirable properties; in particular they can fully describe conditional independences from directed acyclic graphs (DAGs) in the presence of latent and selection variables. However, different MAGs…

Combinatorics · Mathematics 2020-07-07 Zhongyi Hu , Robin Evans

Graphical models are popular statistical tools which are used to represent dependent or causal complex systems. Statistically equivalent causal or directed graphical models are said to belong to a Markov equivalent class. It is of great…

Machine Learning · Statistics 2014-01-30 Yangbo He , Jinzhu Jia , Bin Yu

Two directed acyclic graphs (DAGs) are called Markov equivalent if and only if they have the same underlying undirected graph (i.e. skeleton) and the same set of immoralities. Using observational data, a DAG model can only be determined up…

Combinatorics · Mathematics 2017-06-20 Adityanarayanan Radhakrishnan , Liam Solus , Caroline Uhler

Graphical Markov models combine conditional independence constraints with graphical representations of stepwise data generating processes.The models started to be formulated about 40 years ago and vigorous development is ongoing.…

Methodology · Statistics 2015-10-12 Nanny Wermuth

The sizes of Markov equivalence classes of directed acyclic graphs play important roles in measuring the uncertainty and complexity in causal learning. A Markov equivalence class can be represented by an essential graph and its undirected…

Machine Learning · Statistics 2016-10-26 Yangbo He , Bin Yu

We initiate the study of counting Markov Equivalence Classes (MEC) under logical constraints. MECs are equivalence classes of Directed Acyclic Graphs (DAGs) that encode the same conditional independence structure among the random variables…

Logic in Computer Science · Computer Science 2024-05-24 Davide Bizzaro , Luciano Serafini , Sagar Malhotra

Although the concept of d-separation was originally defined for directed acyclic graphs (see Pearl 1988), there is a natural extension of he concept to directed cyclic graphs. When exactly the same set of d-separation relations hold in two…

Artificial Intelligence · Computer Science 2013-02-18 Thomas S. Richardson

Ordered sequences of univariate or multivariate regressions provide statistical models for analysing data from randomized, possibly sequential interventions, from cohort or multi-wave panel studies, but also from cross-sectional or…

Methodology · Statistics 2015-03-19 Nanny Wermuth , Kayvan Sadeghi

We study the problem of restricting a Markov equivalence class of maximal ancestral graphs (MAGs) to only those MAGs that contain certain edge marks, which we refer to as expert or orientation knowledge. Such a restriction of the Markov…

Machine Learning · Statistics 2025-09-26 Aparajithan Venkateswaran , Emilija Perković
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