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'.

Version:	1.0
Imports:	Rcpp, sparvaride
LinkingTo:	Rcpp, RcppArmadillo
Published:	2026-10-29
DOI:	10.32614/CRAN.package.glt (may not be active yet)
Author:	Antonio Canale [aut, cre]
Maintainer:	Antonio Canale <antonio.canale at unipd.it>
License:	GPL-2
NeedsCompilation:	yes
Materials:	README
CRAN checks:	glt results

Documentation:

Reference manual:

glt.html , glt.pdf

Downloads:

Package source:	glt_1.0.tar.gz
Windows binaries:	r-devel: glt_1.0.zip, r-release: glt_1.0.zip, r-oldrel: not available
macOS binaries:	r-release (arm64): glt_1.0.tgz, r-oldrel (arm64): glt_1.0.tgz, r-release (x86_64): glt_1.0.tgz, r-oldrel (x86_64): glt_1.0.tgz

Linking:

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