CRAN/E | lori

lori

Imputation of High-Dimensional Count Data using Side Information

Installation

About

Analysis, imputation, and multiple imputation of count data using covariates. LORI uses a log-linear Poisson model where main row and column effects, as well as effects of known covariates and interaction terms can be fitted. The estimation procedure is based on the convex optimization of the Poisson loss penalized by a Lasso type penalty and a nuclear norm. LORI returns estimates of main effects, covariate effects and interactions, as well as an imputed count table. The package also contains a multiple imputation procedure. The methods are described in Robin, Josse, Moulines and Sardy (2019) .

Key Metrics

Version 2.2.2
R ≥ 2.10
Published 2020-12-16 1232 days ago
Needs compilation? no
License GPL-3
CRAN checks lori results

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Maintainer

Maintainer

Genevieve Robin

genevieve.robin@cnrs.fr

Authors

Genevieve Robin

aut / cre

Material

README
Reference manual
Package source

In Views

MissingData

Vignettes

aravo_data_analysis
getting_started

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

lori archive

Depends

stats
data.table
rARPACK
svd
R ≥ 2.10

Suggests

knitr
rmarkdown
testthat