Package: missForestPredict 1.0

Elena Albu

missForestPredict: Missing Value Imputation using Random Forest for Prediction Settings

Missing data imputation based on the 'missForest' algorithm (Stekhoven, Daniel J (2012) <doi:10.1093/bioinformatics/btr597>) with adaptations for prediction settings. The function missForest() is used to impute a (training) dataset with missing values and to learn imputation models that can be later used for imputing new observations. The function missForestPredict() is used to impute one or multiple new observations (test set) using the models learned on the training data.

Authors:Elena Albu [aut, cre]

missForestPredict_1.0.tar.gz
missForestPredict_1.0.zip(r-4.5)missForestPredict_1.0.zip(r-4.4)missForestPredict_1.0.zip(r-4.3)
missForestPredict_1.0.tgz(r-4.5-any)missForestPredict_1.0.tgz(r-4.4-any)missForestPredict_1.0.tgz(r-4.3-any)
missForestPredict_1.0.tar.gz(r-4.5-noble)missForestPredict_1.0.tar.gz(r-4.4-noble)
missForestPredict_1.0.tgz(r-4.4-emscripten)missForestPredict_1.0.tgz(r-4.3-emscripten)
missForestPredict.pdf |missForestPredict.html
missForestPredict/json (API)

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

Bug tracker:https://github.com/sibipx/missforestpredict/issues

On CRAN:

Conda:

4.00 score 3 scripts 211 downloads 8 exports 5 dependencies

Last updated 1 years agofrom:0ed4a3ae48. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 07 2025
R-4.5-winOKMar 07 2025
R-4.5-macOKMar 07 2025
R-4.5-linuxOKMar 07 2025
R-4.4-winOKMar 07 2025
R-4.4-macOKMar 07 2025
R-4.4-linuxOKMar 07 2025
R-4.3-winOKMar 07 2025
R-4.3-macOKMar 07 2025

Exports:calculate_convergencecheck_predictor_matrixcreate_predictor_matrixevaluate_imputation_errormissForestmissForestPredictproduce_NAprop_usable_cases

Dependencies:latticeMatrixrangerRcppRcppEigen

missForestPredict convergence criteria and error monitoring

Rendered frommissForestPredict_convergence_criteria_and_error_monitoring.Rmdusingknitr::rmarkdownon Mar 07 2025.

Last update: 2023-12-08
Started: 2022-02-09

Using the missForestPredict package

Rendered frommissForestPredict_usage.Rmdusingknitr::rmarkdownon Mar 07 2025.

Last update: 2023-12-11
Started: 2022-01-25