Package: Iscores 1.2.0

Krystyna Grzesiak

Iscores: Proper Scoring Rules for Missing Value Imputation

Provides tools for evaluating and ranking missing value imputation methods using proper scoring rules. Implements the Energy-I-Score and the DR-I-Score for the assessment of deterministic, stochastic and multiple imputation methods for numerical and mixed datasets, following Näf et al. (2022) <doi:10.48550/arXiv.2106.03742> and Näf et al. (2025) <doi:10.48550/arXiv.2507.11297>.

Authors:Krystyna Grzesiak [aut, cre], Loris Michel [aut, ctb], Meta-Lina Spohn [aut, ctb], Jeffrey Näf [aut, ctb]

Iscores_1.2.0.tar.gz
Iscores_1.2.0.tar.gz(r-4.7-any)Iscores_1.2.0.tar.gz(r-4.6-any)
Iscores_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
Iscores/json (API)

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

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

Pkgdown/docs site:https://krystynagrzesiak.github.io

On CRAN:

Conda:

3.23 score 17 scripts 68 downloads 9 exports 19 dependencies

Last updated from:861592d82a. Checks:4 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK351
source / vignettesOK213
linux-release-x86_64OK356
wasm-releaseOK130

Exports:compare_IscoresDR_IScoreedistanceenergy_IScoreexp_imputationmedian_mode_imputationnorm_imputationrandom_mcar_datarandom_mcar_mixed_data

Dependencies:bootenergyevaluategslhighrkernlabknitrlatticeMASSMatrixpbapplypbmcapplyrangerRcppRcppArmadilloRcppEigenscoringRulesxfunyaml

Energy-I-Score: First Steps

Rendered fromExample_IScore.Rmdusingknitr::rmarkdownon Jun 08 2026.

Last update: 2026-06-08
Started: 2026-06-08

Energy-I-Score: Implementation Details

Rendered fromAbout_IScore.Rmdusingknitr::rmarkdownon Jun 08 2026.

Last update: 2026-06-08
Started: 2026-06-08