Package: imputeR 2.2

imputeR: A General Multivariate Imputation Framework

Multivariate Expectation-Maximization (EM) based imputation framework that offers several different algorithms. These include regularisation methods like Lasso and Ridge regression, tree-based models and dimensionality reduction methods like PCA and PLS.

Authors:Steffen Moritz [aut, cre], Lingbing Feng [aut], Gen Nowak [ctb], Alan. H. Welsh [ctb], Terry. J. O'Neill [ctb]

imputeR_2.2.tar.gz
imputeR_2.2.zip(r-4.5)imputeR_2.2.zip(r-4.4)imputeR_2.2.zip(r-4.3)
imputeR_2.2.tgz(r-4.4-any)imputeR_2.2.tgz(r-4.3-any)
imputeR_2.2.tar.gz(r-4.5-noble)imputeR_2.2.tar.gz(r-4.4-noble)
imputeR_2.2.tgz(r-4.4-emscripten)imputeR_2.2.tgz(r-4.3-emscripten)
imputeR.pdf |imputeR.html
imputeR/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/steffenmoritz/imputer/issues

Datasets:
  • parkinson - Parkinsons Data Set
  • spect - SPECT Heart Data Set
  • tic - Insurance Company Benchmark (COIL 2000) Data Set

On CRAN:

missing-data

4.90 score 16 stars 50 scripts 283 downloads 1 mentions 28 exports 11 dependencies

Last updated 3 years agofrom:beda0d1053. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-winOKNov 03 2024
R-4.5-linuxOKNov 03 2024
R-4.4-winOKNov 03 2024
R-4.4-macOKNov 03 2024
R-4.3-winOKNov 03 2024
R-4.3-macOKNov 03 2024

Exports:CubistRDetectgbmCglmboostRguessimputelassoClassoRmajormixErrormixGuessmrorderboxpcrRplotImplsRridgeCridgeRRmserpartCSimEvalSimImstepBackCstepBackRstepBothCstepBothRstepForCstepForR

Dependencies:cligluelifecyclemagrittrplyrRcppreshape2rlangstringistringrvctrs