colvR: Poisson Lognormal with Dimension Reduction for Count Matrices with Missing Data

Impute missing data in count tables using a Poisson lognormal model with dimension reduction, with and without zero inflation, as described in Bricout et al. (2026) <doi:10.48550/arXiv.2602.10673>. Parameters are estimated with a variational expectation-maximization algorithm. The package also provides the asymptotic variance of the estimators, prediction intervals for the imputed counts, and model selection criteria (Bayesian information criterion, BIC, and integrated completed likelihood, ICL) to choose the dimension of the latent space.

Version:	0.2.2
Depends:	R (≥ 3.5)
Imports:	Rcpp, PLNmodels, Matrix, mvtnorm, pbapply, lori, MASS
LinkingTo:	Rcpp, RcppArmadillo, nloptr
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown, spelling
Published:	2026-11-13
DOI:	10.32614/CRAN.package.colvR
Author:	Barbara Bricout [aut, cre]
Maintainer:	Barbara Bricout <barbara.bricout at gmail.com>
BugReports:	https://github.com/BBricout/colvR/issues
License:	GPL (≥ 3)
URL:	https://github.com/BBricout/colvR, https://bbricout.github.io/colvR/
NeedsCompilation:	yes
SystemRequirements:	NLopt, C++17
Language:	en-US
Citation:	colvR citation info
Materials:	README, NEWS
CRAN checks:	colvR results

Documentation:

Reference manual:	colvR.html , colvR.pdf
Vignettes:	Getting started with colvR (source, R code)

Downloads:

Package source:	colvR_0.2.2.tar.gz
Windows binaries:	r-devel: not available, r-release: colvR_0.2.2.zip, r-oldrel: colvR_0.2.2.zip
macOS binaries:	r-release (arm64): colvR_0.2.2.tgz, r-oldrel (arm64): colvR_0.2.2.tgz, r-release (x86_64): colvR_0.2.2.tgz, r-oldrel (x86_64): colvR_0.2.2.tgz
Old sources:	colvR archive

Linking:

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