nference in Graphical Gaussian Models with Edge and Vertex Symmetries with the gRc Package for R

nference in Graphical Gaussian Models with Edge and Vertex Symmetries with the gRc Package for R

In this paper we present the R package gRc for statistical inference in graphical Gaussian models in which symmetry restrictions have been imposed on the concentration or partial correlation matrix. The models are represented by coloured graphs where parameters associated with edges or vertices of s...

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Bibliographic Details
Main Authors: Søren Højsgaard, Steffen L. Lauritzen
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2007-09-01
Series:Journal of Statistical Software
Subjects:
concentration matrix
conditional independence
covariance selection
graphical model
graph
graph colouring
iterative partial maximization
iterative proportional scaling
multivariate normal distribution
partial correlation
Online Access:http://www.jstatsoft.org/v23/i06/paper

Internet

http://www.jstatsoft.org/v23/i06/paper

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