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:

4.00 score 3 scripts 200 downloads 8 exports 5 dependencies

Last updated 1 years agofrom:0ed4a3ae48. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 05 2025
R-4.5-winOKFeb 05 2025
R-4.5-macOKFeb 05 2025
R-4.5-linuxOKFeb 05 2025
R-4.4-winOKFeb 05 2025
R-4.4-macOKFeb 05 2025
R-4.3-winOKFeb 05 2025
R-4.3-macOKFeb 05 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 Feb 05 2025.

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

Using the missForestPredict package

Rendered frommissForestPredict_usage.Rmdusingknitr::rmarkdownon Feb 05 2025.

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