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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

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

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

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

This paper considers the problem of defining distributions over graphical structures. We propose an extension of the hyper Markov properties of Dawid and Lauritzen [Ann. Statist. 21 (1993) 1272-1317], which we term structural Markov…

Statistics Theory · Mathematics 2020-04-28 Simon Byrne , A. Philip Dawid

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

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

We present a new, efficient procedure to establish Markov equivalence between directed graphs that may or may not contain cycles under the \textit{d}-separation criterion. It is based on the Cyclic Equivalence Theorem (CET) in the seminal…

Artificial Intelligence · Computer Science 2023-09-07 Tom Claassen , Joris M. Mooij

It is well known that there may be many causal explanations that are consistent with a given set of data. Recent work has been done to represent the common aspects of these explanations into one representation. In this paper, we address…

Methodology · Statistics 2012-07-09 Ayesha R. Ali , Thomas S. Richardson , Peter L. Spirtes , Jiji Zhang

We propose a generalization of the asymptotic equipartition property to discrete sources with an ambiguous alphabet, and prove that it holds for irreducible stationary Markov sources with an arbitrary distinguishability relation. Our…

Information Theory · Computer Science 2022-07-29 Tamás Tasnádi , Péter Vrana

Using the renewal approach we prove exponential inequalities for additive functionals and empirical processes of ergodic Markov chains, thus obtaining counterparts of inequalities for sums of independent random variables. The inequalities…

Probability · Mathematics 2013-10-18 Radosław Adamczak , Witold Bednorz

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

In this paper we discuss four problems regarding Markov equivalences for subclasses of loopless mixed graphs. We classify these four problems as finding conditions for internal Markov equivalence, which is Markov equivalence within a…

Other Statistics · Statistics 2011-10-21 Kayvan Sadeghi

Graph comparison is a certain type of condition on metric space encoded by a finite graph. We show that any nontrivial graph comparison implies one of Alexandrov's comparisons. The proof gives a complete description of graphs with trivial…

Metric Geometry · Mathematics 2023-06-13 Nina Lebedeva , Anton Petrunin

Drawing on some recent results that provide the formalism necessary to definite stationarity for infinite random graphs, this paper initiates the study of statistical and learning questions pertaining to these objects. Specifically, a…

Machine Learning · Computer Science 2017-08-11 Daniil Ryabko

We introduce a new definition of exponential family of Markov chains, and show that many characteristic properties of the usual exponential family of probability distributions are properly extended to Markov chains. The method of…

Information Theory · Computer Science 2017-01-24 Hiroshi Nagaoka

This supplementary material includes three parts: some preliminary results, four examples, an experiment, three new algorithms, and all proofs of the results in the paper "Reversible MCMC on Markov equivalence classes of sparse directed…

Machine Learning · Statistics 2013-08-13 Yangbo He , Jinzhu Jia , Bin Yu

We give some properties of skew spectrum of a graph, especially, we answer negatively a problem concerning the skew characteristic polynomial and matching polynomial in [M. Cavers et al., Skew-adjacency matrices of graphs, Linear Algebra…

Combinatorics · Mathematics 2013-10-29 Yanna Wang , Bo Zhou

The exponential rate of convergence for some Markov operators is established. The operators correspond to continuous iterated function systems which are a very useful tool in some cell cycle models.

Probability · Mathematics 2016-03-23 Hanna Wojewódka

We provide necessary and sufficient conditions for convergence of exponential integrals of Markov additive processes. Other than in the classical L\'evy case studied by Erickson and Maller we have to distinguish between almost sure…

Probability · Mathematics 2020-03-06 Anita Behme , Apostolos Sideris
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