Package: glt 1.0

Antonio Canale

glt: Bayesian Factor Modelling via Generalized Lower Triangular Priors

Sparse Bayesian factor models for multivariate data, built around a flexible Generalized Lower Triangular (GLT) process prior on the loading matrix by Canale and Frühwirth-Schnatter (2026) <doi:10.48550/arXiv.2610.09762>. The number of active factors, their sparsity pattern, and the loadings themselves are learned jointly via a Markov chain Monte Carlo sampler implemented in C++ with 'Rcpp' and 'RcppArmadillo'.

Authors:Antonio Canale [aut, cre]

glt_1.0.tar.gz
glt_1.0.zip(r-4.7-x86_64)glt_1.0.zip(r-4.7-arm64)glt_1.0.zip(r-4.6-x86_64)glt_1.0.zip(r-4.6-arm64)
glt_1.0.tar.gz(r-4.7-arm64)glt_1.0.tar.gz(r-4.7-x86_64)glt_1.0.tar.gz(r-4.6-arm64)glt_1.0.tar.gz(r-4.6-x86_64)
glt_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
glt/json (API)

# Install 'glt' in R:
install.packages('glt', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • 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.

openblascpp

1.70 score 6 exports 3 dependencies

Last updated from:3c27f9e9e8. Checks:10 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK130
linux-devel-x86_64OK134
source / vignettesOK241
linux-release-arm64OK127
linux-release-x86_64OK158
windows-devel-arm64OK299
windows-devel-x86_64OK212
windows-release-arm64OK292
windows-release-x86_64OK209
wasm-releaseOK145

Exports:facmatrixget_pivotsget_variancegltfagltfa_starplot_real_matrix

Dependencies:RcppRcppArmadillosparvaride