Implement some models for correlation/covariance matrices including two approaches to model correlation matrices from a graphical structure. One use latent parent variables as proposed in Sterrantino et. al. (2024) <doi:10.1007/s10260-025-00788-y>. The other uses a graph to specify conditional relations between the variables. The graphical structure makes correlation matrices interpretable and avoids the quadratic increase of parameters as a function of the dimension. In the first approach a natural sequence of simpler models along with a complexity penalization is used. The second penalizes deviations from a base model. These can be used as prior for model parameters, considering C code through the 'cgeneric' interface for the 'INLA' package (<https://www.r-inla.org>). This allows one to use these models as building blocks combined and to other latent Gaussian models in order to build complex data models.
| Version: | 0.1.25 |
| Depends: | R (≥ 4.3), Matrix, INLAtools (> 0.1.3), numDeriv |
| Imports: | methods, stats, utils, igraph |
| Suggests: | knitr, INLA (≥ 24.02.09) |
| Published: | 2026-05-07 |
| DOI: | 10.32614/CRAN.package.graphpcor |
| Author: | Elias Teixeira Krainski
|
| Maintainer: | Elias Teixeira Krainski <elias.krainski at kaust.edu.sa> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| Additional_repositories: | https://inla.r-inla-download.org/R/testing |
| CRAN checks: | graphpcor results |
| Reference manual: | graphpcor.html , graphpcor.pdf |
| Vignettes: |
Tree based latent variables correlation model (source, R code) |
| Package source: | graphpcor_0.1.25.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): graphpcor_0.1.25.tgz, r-oldrel (x86_64): not available |
| Old sources: | graphpcor archive |
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