Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R
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Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R. / Hojsgaard, Soren; Lauritzen, Steffen L.
In: Journal of Statistical Software, Vol. 23, No. 6, 2007.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R
AU - Hojsgaard, Soren
AU - Lauritzen, Steffen L.
PY - 2007
Y1 - 2007
N2 - 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 same colour are restricted to being identical. We describe algorithms for maximum likelihood estimation and discuss model selection issues. The paper illustrates the practical use of the gRc package.
AB - 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 same colour are restricted to being identical. We describe algorithms for maximum likelihood estimation and discuss model selection issues. The paper illustrates the practical use of the gRc package.
M3 - Journal article
VL - 23
JO - Journal of Statistical Software
JF - Journal of Statistical Software
SN - 1548-7660
IS - 6
ER -
ID: 127620879