Package: Iscores 1.1.0

Loris Michel

Iscores: Proper Scoring Rules for Missing Value Imputation

Implementation of a KL-based scoring rule to assess the quality of different missing value imputations in the broad sense as introduced in Michel et al. (2021) <arxiv:2106.03742>.

Authors:Loris Michel, Meta-Lina Spohn, Jeffrey Naef

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Iscores.pdf |Iscores.html✨
Iscores/json (API)

# Install 'Iscores' in R:
install.packages('Iscores', repos = c('https://missvalteam.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/missvalteam/iscores/issues

On CRAN:

Conda:

imputation-methodsmachine-learningmissing-valuesrandom-forest

3.91 score 7 stars 23 scripts 204 downloads 1 exports 6 dependencies

Last updated 2 years agofrom:c4fb5184ec. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 12 2025
R-4.5-winOKMar 12 2025
R-4.5-macOKMar 12 2025
R-4.5-linuxOKMar 12 2025
R-4.4-winOKMar 12 2025
R-4.4-macOKMar 12 2025
R-4.4-linuxOKMar 12 2025
R-4.3-winOKMar 12 2025
R-4.3-macOKMar 12 2025

Exports:Iscores

Dependencies:kernlablatticeMatrixrangerRcppRcppEigen