Search Results - subject:"Graphical Models"

On the Intersection Property of Conditional Independence and its Application to Causal Discovery

Peters, Jonas - In: Journal of Causal Inference 3 (2015) 1, pp. 97-108

Abstract This work investigates the intersection property of conditional independence. It states that for random variables $$A,B,C$$ and X we have that $$X \bot \bot A{\kern 1pt} {\kern 1pt} |{\kern 1pt} {\kern 1pt} B,C$$ and $$X\, \bot \bot\, B{\kern 1pt} {\kern 1pt} |{\kern 1pt} {\kern 1pt}...

Persistent link: https://www.econbiz.de/10014610812

Bayesian structure learning in graphical models

Banerjee, Sayantan; Ghosal, Subhashis - In: Journal of Multivariate Analysis 136 (2015) C, pp. 147-162

dimension p may be large. Gaussian graphical models provide an important tool in describing conditional independence through …

Persistent link: https://www.econbiz.de/10011208468

Fast and adaptive sparse precision matrix estimation in high dimensions

Liu, Weidong; Luo, Xi - In: Journal of Multivariate Analysis 135 (2015) C, pp. 153-162

This paper proposes a new method for estimating sparse precision matrices in the high dimensional setting. It has been popular to study fast computation and adaptive procedures for this problem. We propose a novel approach, called Sparse Column-wise Inverse Operator, to address these two issues....

Persistent link: https://www.econbiz.de/10011189572

Towards Inference and Learning in Dynamic Bayesian Networks using Generalized Evidence

Langmead, Christopher J. - 2008

This report introduces a novel approach to performing inference and learning in Dynamic Bayesian Networks (DBN). The traditional approach to inference and learning in DBNs involves conditioning on one or more finite-length observation sequences. In this report, we consider conditioning on what...

Persistent link: https://www.econbiz.de/10009441211

A Third-Order Item Response Theory Model for Modeling the Effects of Domains and Subdomains in Large-Scale Educational Assessment Surveys

Rijmen, Frank; Jeon, Minjeong; Davier, Matthias von; … - In: Journal of Educational and Behavioral Statistics 39 (2014) 4, pp. 235-256

Second-order item response theory models have been used for assessments consisting of several domains, such as content areas. We extend the second-order model to a third-order model for assessments that include subdomains nested in domains. Using a graphical model framework, it is shown how the...

Persistent link: https://www.econbiz.de/10010894047

Bayesian Covariance Matrix Estimation using a Mixture of Decomposable Graphical Models

Armstrong, Helen; Carter, Christopher K.; Wong, Kevin K. F. - School of Economics, UNSW Business School - 2007

ideas from Gaussian graphical models and model selection to construct a prior for the covariance matrix that is a mixture …-8949 ISBN 978 0 7334 2449 6 Bayesian Covariance Matrix Estimation using a Mixture of Decomposable Graphical Models … at UNSW. Bayesian Covariance Matrix Estimation using a Mixture of Decomposable Graphical Models Helen Armstrong School …

Persistent link: https://www.econbiz.de/10005135157

Paradata and Bayesian networks: a tool for monitoring and troubleshooting the data production process

Ballin, Marco; Scanu, Mauro; Vicard, Paola - Dipartimento di Economia, Università degli Studi di Roma 3 - 2006

The problem of monitoring and managing the data production process by means of process flow indicators is presented in a decision theory framework. Here it is shown how to represent and solve the decision problem via influence diagrams, i.e. Bayesian network supporting decisions. An illustrative...

Persistent link: https://www.econbiz.de/10005590597

Robust methods for inferring sparse network structures

Vinciotti, Veronica; Hashem, Hussein - In: Computational Statistics & Data Analysis 67 (2013) C, pp. 84-94

Networks appear in many fields, from finance to medicine, engineering, biology and social science. They often comprise of a very large number of entities, the nodes, and the interest lies in inferring the interactions between these entities, the edges, from relatively limited data. If the...

Persistent link: https://www.econbiz.de/10010871363

Efficient identification of independence networks using mutual information

Bacciu, Davide; Etchells, Terence; Lisboa, Paulo; … - In: Computational Statistics 28 (2013) 2, pp. 621-646

Conditional independence graphs are now widely applied in science and industry to display interactions between large numbers of variables. However, the computational load of structure identification grows with the number of nodes in the network and the sample size. A tailored version of the PC...

Persistent link: https://www.econbiz.de/10010847801

Bayesian analysis of latent threshold dynamic models

Nakajima, Jouchi; West, Mike - In: Journal of business & economic statistics : JBES ; a … 31 (2013) 2, pp. 151-164

Persistent link: https://www.econbiz.de/10009754013