Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R

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Standard

Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R. / Hojsgaard, Soren; Lauritzen, Steffen L.

I: Journal of Statistical Software, Bind 23, Nr. 6, 2007.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Hojsgaard, S & Lauritzen, SL 2007, 'Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R', Journal of Statistical Software, bind 23, nr. 6.

APA

Hojsgaard, S., & Lauritzen, S. L. (2007). Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R. Journal of Statistical Software, 23(6).

Vancouver

Hojsgaard S, Lauritzen SL. Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R. Journal of Statistical Software. 2007;23(6).

Author

Hojsgaard, Soren ; Lauritzen, Steffen L. / Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R. I: Journal of Statistical Software. 2007 ; Bind 23, Nr. 6.

Bibtex

@article{1fe4ede52dd74f62a7562be3f54ecf03,
title = "Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R",
abstract = "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.",
author = "Soren Hojsgaard and Lauritzen, {Steffen L.}",
year = "2007",
language = "English",
volume = "23",
journal = "Journal of Statistical Software",
issn = "1548-7660",
publisher = "The Foundation for Open Access Statistics",
number = "6",

}

RIS

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