Package: normalblockr 0.3.0

Julien Chiquet

normalblockr: Gaussian Graphical Models with Latent Clustering Structure

Implements the Normal-Block model, a Gaussian graphical model with a latent clustering structure for the multivariate analysis of continuous data. The model clusters variables and, building on the graphical lasso, infers a network of statistical dependencies between clusters rather than between individual variables, for known or unknown clusterings, with an optional zero-inflation extension for data with an excess of exact zeros. A complementary family clusters variables by their regression response to covariates rather than by their covariance, sharing one profile per cluster. See Tous & Chiquet (2026) <doi:10.1016/j.csda.2026.108347> for the model itself and its variational expectation-maximization estimation procedure.

Authors:Jeanne Tous [aut], Nestor Ngalala Manguitini [ctb], Julien Chiquet [aut, cre]

normalblockr_0.3.0.tar.gz
normalblockr_0.3.0.zip(r-4.7-x86_64)normalblockr_0.3.0.zip(r-4.7-arm64)normalblockr_0.3.0.zip(r-4.6-x86_64)normalblockr_0.3.0.zip(r-4.6-arm64)
normalblockr_0.3.0.tar.gz(r-4.7-arm64)normalblockr_0.3.0.tar.gz(r-4.7-x86_64)normalblockr_0.3.0.tar.gz(r-4.6-arm64)normalblockr_0.3.0.tar.gz(r-4.6-x86_64)
normalblockr_0.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
normalblockr/json (API)

# Install 'normalblockr' in R:
install.packages('normalblockr', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jchiquet/normalblockr/issues

Pkgdown/docs site:https://jchiquet.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • brca_rppa - Breast cancer proteomics data
  • onema - French stream fish community data
  • university - University webpages text data

On CRAN:

Conda:

openblascpp

3.83 score 17 scripts 644 downloads 22 exports 61 dependencies

Last updated from:7ab4554930. Checks:4 ERROR, 6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64ERROR163
linux-devel-x86_64OK185
source / vignettesOK248
linux-release-arm64ERROR166
linux-release-x86_64OK198
windows-devel-arm64ERROR292
windows-devel-x86_64OK225
windows-release-arm64ERROR244
windows-release-x86_64OK190
wasm-releaseOK129

Exports:generate_normal_block_mean_datagenerate_normal_block_var_dataget_modelisNBNB_controlnormal_blocknormal_block_sequentialNormalBlockDataNormalBlockMeanCollectionClustersNormalBlockMeanCollectionClustersSparsityNormalBlockMeanCollectionSparsityNormalBlockMeanKnownClustersNormalBlockMeanUnknownClustersNormalBlockVarCollectionClustersNormalBlockVarCollectionClustersSparsityNormalBlockVarCollectionSparsityNormalBlockVarKnownClustersNormalBlockVarUnknownClustersZINormalBlockMeanKnownClustersZINormalBlockMeanUnknownClustersZINormalBlockVarKnownClustersZINormalBlockVarUnknownClusters

Dependencies:alluvialaricodeblockmodelsclicodetoolscorrplotcpp11data.tablediagramdigestdplyrfarverfuturefuture.applygenericsggplot2globalsglueGREMLINSgtableigraphisobandKernSmoothlabelinglatticelavalifecyclelistenvmagrittrMASSMatrixnumDerivparallellypbmcapplypillarpkgconfigplyrprodlimprogressrpurrrR6RColorBrewerRcppRcppArmadilloreshape2rlangS7sbmscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

Analyzing multivariate Gaussian data with the Normal-Block model (variance clustering) - First steps
Preliminaries | Requirements | Data simulation | Fix simulation parameters | Simulation 1 (no zero-inflation) | Simulation 2 (with zero-inflation) | Prepare the data for a Normal-Block analysis | Run a Normal-Block analysis | With non-zero-inflated data | Fixed clustering | Fixed number of clusters | Unknown number of clusters | Playing with sparsity | With zero-inflated data | References
Rendered fromnormal-block.Rmdusingknitr::rmarkdown

Last update: 2026-09-11
Started: 2026-09-03

Mean-Block models: clustering variables by their response to covariates
Preliminaries | Mathematical background | The data | A known clustering | Letting the model infer the clustering | A collection over the number of clusters | Reading the clusters | Choosing the shape of the residual covariance | Sparsifying the residual covariance | References
Rendered frommean-block-breast-cancer.Rmdusingknitr::rmarkdown

Last update: 2026-09-11
Started: 2026-09-11

Normal-Block models: clustering variables by their covariance -- a worked example with breast cancer proteomics data
Preliminaries | Requirements | Mathematical background | The data | A known clustering of the proteins | Letting the model infer its own clustering | Fitting a collection over a range of cluster counts | Model selection: criteria to fix the number of clusters | Refining the clustering | Sparsifying the network of the selected clustering | References
Rendered frombreast-cancer-proteomics.Rmdusingknitr::rmarkdown

Last update: 2026-09-11
Started: 2026-09-03

Zero-inflated Normal-Block models (variance clustering): a worked example with fish biomass data
Preliminaries | Mathematical background | The Normal-Block model | Zero-inflation extension | The zero-inflation probabilities $\kappa$ | Requirements | The data | Preparing the data | Fitting a zero-inflated Normal-Block model | Refining the collection | Selecting a model and inspecting the clustering | Inspecting the zero-inflation probabilities | Sparsifying the association network | References
Rendered fromzero-inflated-normal-block.Rmdusingknitr::rmarkdown

Last update: 2026-09-11
Started: 2026-09-03

Readme and manuals

Help Manual

Help pageTopics
Bayesian Information Criterion for a Normal-Block ModelBIC.NormalBlockBase
Bayesian Information Criterion for a Collection of Normal-Block ModelsBIC.NormalBlockCollection
Breast cancer proteomics data (TCGA, RPPA)brca_rppa
Extract Model Coefficientscoef.NormalBlockBase
Extract Fitted Valuesfitted.NormalBlockBase
Generate Normal Block Mean Datagenerate_normal_block_mean_data
Generate Normal Block Var Datagenerate_normal_block_var_data
Create a Normal-Block Model Objectget_model
Check if an Object is a Normal-Block ModelisNB
Extract Log-Likelihood of a Normal-Block ModellogLik.NormalBlockBase
Extract Log-Likelihood of a Collection of Normal-Block ModelslogLik.NormalBlockCollection
NB_controlNB_control
Normal-block modelnormal_block
Cluster variables in the mean, then in the residual covariancenormal_block_sequential
Data Container for Normal-Block ModelsNormalBlockData
Collection of Mean-Block Models over a Range of Cluster CountsNormalBlockMeanCollectionClusters
Collection of Mean-Block Models over Cluster Counts and Sparsity LevelsNormalBlockMeanCollectionClustersSparsity
Collection of Mean-Block Models over a Sparsity PathNormalBlockMeanCollectionSparsity
Mean-Block Model with Known ClusteringNormalBlockMeanKnownClusters
Mean-Block Model with Unknown ClusteringNormalBlockMeanUnknownClusters
Collection of Normal-Block Models over a Range of Cluster CountsNormalBlockVarCollectionClusters
Collection of Normal-Block Models over Cluster Counts and Sparsity LevelsNormalBlockVarCollectionClustersSparsity
Collection of Normal-Block Models over a Sparsity PathNormalBlockVarCollectionSparsity
Normal-Block Model with Known ClusteringNormalBlockVarKnownClusters
Normal-Block Model with Unknown ClusteringNormalBlockVarUnknownClusters
French stream fish community data (ONEMA / OFB electrofishing surveys)onema
Plot a Normal-Block Modelplot.NormalBlockBase
Predict Method for Variance-Block Modelspredict.NormalBlockBase
Print a Sequential Mean-then-Variance Fitprint.normal_block_sequential
Print a Normal-Block Modelprint.NormalBlockBase
Print a Collection of Normal-Block Modelsprint.NormalBlockCollection
Print a Normal-Block Model Summaryprint.summary.NormalBlockBase
Print a Collection Summaryprint.summary.NormalBlockCollection
Extract the Covariance Matrixsigma.NormalBlockBase
Summarize a Normal-Block Modelsummary.NormalBlockBase
Summarize a Collection of Normal-Block Modelssummary.NormalBlockCollection
University webpages text data (CMU "4 Universities" / WebKB)university
Zero-Inflated Mean-Block Model with Known ClusteringZINormalBlockMeanKnownClusters
Zero-Inflated Mean-Block Model with Unknown ClusteringZINormalBlockMeanUnknownClusters
Zero-Inflated Normal-Block Model with Known ClusteringZINormalBlockVarKnownClusters
Zero-Inflated Normal-Block Model with Unknown ClusteringZINormalBlockVarUnknownClusters