Package: GWnorm 1.0.1

GWnorm: G-Wishart Normalising Constants for Gaussian Graphical Models

Computes G-Wishart normalising constants through a Fourier approach. Either exact analytical results, numerical integration or Monte Carlo estimation are employed. Details at C. Wong, G. Moffa and J. Kuipers (2024), <doi:10.48550/arXiv.2404.06803>. Also includes approximations of the ratio of normalising constants, see details at C. Wong, G. Moffa and J. Kuipers (2025), <doi:10.48550/arXiv.2503.13046>.

Authors:Ching Wong [aut], Jack Kuipers [aut, cre]

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manual.pdf |manual.html✨
card.svg |card.png
GWnorm/json (API)

# Install 'GWnorm' in R:
install.packages('GWnorm', repos = c('https://jackkuipers.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

1.30 score 483 downloads 17 exports 34 dependencies

Last updated from:3f7569e7b5. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK180
linux-devel-x86_64OK147
source / vignettesOK317
linux-release-arm64OK173
linux-release-x86_64OK149
macos-release-arm64OK160
macos-release-x86_64OK241
macos-oldrel-arm64OK138
macos-oldrel-x86_64OK270
windows-develOK104
windows-releaseOK111
windows-oldrelOK102
wasm-releaseOK141

Exports:C_GtoI_Gcheck_prime_connectedI_G_BDI_G_chordalI_G_completeI_G_MCI_G_ratio_approxI_G_ratio_approx_primeI_G_specialI_GnormI_GtoC_Gis_6_cycleis_k_partiteIss_cmatIss_matPD_completeprime_decomp

Dependencies:BDgraphCholWishartclicontfraccpp11deSolveellipticfarverggplot2gluegslgtablehypergeoigraphisobandlabelinglatticelifecyclemagrittrMASSMatrixmvtnormpkgconfigpROCR6RColorBrewerRcppRcppEigenrlangS7scalesvctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
this helper function adds information to cliques related to the missing edgesannotate_cliques
This function returns the log of the G-Wishart normalising constant I_G(beta, D) = int_[S^p_++(G)] det(K)^beta * exp(-tr(KD)) dK from the transformed version log(C_G(delta, D)) = int_[S^p_++(G)] det(K)^((delta-2)/2) * exp(-tr(KD)/2) dKC_GtoI_G
This function just checks if a graph is connected and primecheck_prime_connected
Chordal Factor # do not exportchordal_factor
Clique-completionClique_complete
Newton-Raphson update for the clique-completionclique_update_D
Find triangle contains two missing edges # do not exportform_triangle
This function is a wrapper for BDgraph to compare and to avoid the NOTE in the package checks since we only had BDgraph in the examplesI_G_BD
G Wishart normalising constant for chordal graphsI_G_chordal
G Wishart normalising constant for complete graphsI_G_complete
G Wishart normalising constant through MC integrationI_G_MC
G Wishart normalising constantI_G_ratio_approx
This function returns the approximation of the ratio of log transformed G-Wishart normalising constants I_G(beta, D) / I_G(beta, I) for connected prime graphs G. If there is no explicit formula, the approximation is used. Note that this is the same as the ratio C_G(delta, D) / C_G(delta, I) with delta = 2*beta + 2I_G_ratio_approx_prime
G Wishart normalising constant for special casesI_G_special
G Wishart normalising constantI_Gnorm
This function returns the log of the G-Wishart normalising constant log(C_G(delta, D)) = int_[S^p_++(G)] det(K)^((delta-2)/2) * exp(-tr(KD)/2) dK from the transformed version I_G(beta, D) = int_[S^p_++(G)] det(K)^beta * exp(-tr(KD)) dKI_GtoC_G
Determine whether the graph is the cycle of length 6 or its complementis_6_cycle
Determine whether the graph is complete k partiteis_k_partite
Isserlis complement matrixIss_cmat
Isserlis matrixIss_mat
Compute means and gradients for the Newton-Raphson update for the clique-completionlocal_mean_grad
Compute second moment of the log expansion of the determinant (assuming the mean is 0 from Clique_completion)local_precision
PD-completionPD_complete
Predict Row # do not exportpredict_row
Prime Decompositionprime_decomp