Inference 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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| Format: | Journal article |
| Language: | English |
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2007
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| _version_ | 1797077699249831936 |
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| author | Hojsgaard, S Lauritzen, S |
| author_facet | Hojsgaard, S Lauritzen, S |
| author_sort | Hojsgaard, S |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-07T00:21:44Z |
| format | Journal article |
| id | oxford-uuid:7cc84290-a4f5-4910-8510-8741115a8636 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T00:21:44Z |
| publishDate | 2007 |
| record_format | dspace |
| spelling | oxford-uuid:7cc84290-a4f5-4910-8510-8741115a86362022-03-26T20:59:11ZInference in graphical Gaussian models with edge and vertex symmetries with the gRc package for RJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:7cc84290-a4f5-4910-8510-8741115a8636EnglishSymplectic Elements at Oxford2007Hojsgaard, SLauritzen, SIn 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. |
| spellingShingle | Hojsgaard, S Lauritzen, S Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R |
| title | Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R |
| title_full | Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R |
| title_fullStr | Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R |
| title_full_unstemmed | Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R |
| title_short | Inference in graphical Gaussian models with edge and vertex symmetries with the gRc package for R |
| title_sort | inference in graphical gaussian models with edge and vertex symmetries with the grc package for r |
| work_keys_str_mv | AT hojsgaards inferenceingraphicalgaussianmodelswithedgeandvertexsymmetrieswiththegrcpackageforr AT lauritzens inferenceingraphicalgaussianmodelswithedgeandvertexsymmetrieswiththegrcpackageforr |