lori: Low-Rank Interactions in Count Data with Covariates

Analysis, imputation, and multiple imputation of count data using covariates. LORI uses a log-linear model where main row and column effects are decomposed as regression terms on known covariates. A residual low-rank interaction term is also fitted. LORI returns estimates of covariate effects and interactions, as well as an imputed count table. The package also contains a multiple imputation procedure.

Version: 2.0.0
Imports: psych, svd, NLRoot, FactoMineR, glmnet, pdist, lars, ade4, lattice, gridExtra, grid, grDevices, stats, graphics, data.table, doParallel, parallel, corpcor, foreach
Suggests: knitr, rmarkdown, testthat
Published: 2019-02-19
Author: Genevieve Robin [aut, cre]
Maintainer: Genevieve Robin <genevieve.robin at polytechnique.edu>
License: GPL-3
NeedsCompilation: no
Materials: README
In views: MissingData
CRAN checks: lori results

Downloads:

Reference manual: lori.pdf
Vignettes: Analysis of count data with covariates in R using LORI - tutorial
Package source: lori_2.0.0.tar.gz
Windows binaries: r-devel: lori_2.0.0.zip, r-release: lori_2.0.0.zip, r-oldrel: lori_2.0.0.zip
OS X binaries: r-release: lori_2.0.0.tgz, r-oldrel: lori_2.0.0.tgz
Old sources: lori archive

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