Other packages > Find by keyword >

missForestPredict  

Missing Value Imputation using Random Forest for Prediction Settings
View on CRAN: Click here


Download and install missForestPredict package within the R console
Install from CRAN:
install.packages("missForestPredict")

Install from Github:
library("remotes")
install_github("cran/missForestPredict")

Install by package version:
library("remotes")
install_version("missForestPredict", "1.0.1")



Attach the package and use:
library("missForestPredict")
Maintained by
Elena Albu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-12-12
Latest Update: 2025-05-24
Description:
Missing data imputation based on the 'missForest' algorithm (Stekhoven, Daniel J (2012) ) 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.
How to cite:
Elena Albu (2023). missForestPredict: Missing Value Imputation using Random Forest for Prediction Settings. R package version 1.0.1, https://cran.r-project.org/web/packages/missForestPredict. Accessed 05 Jun. 2026.
Previous versions and publish date:
1.0 (2023-12-12 19:20)
Other packages that cited missForestPredict R package
View missForestPredict citation profile
Other R packages that missForestPredict depends, imports, suggests or enhances
Complete documentation for missForestPredict
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
ibb  
R Wrapper for Istanbul Municipality Open Data Portal
Call wrappers for Istanbul Metropolitan Municipality's Open Data Portal (Turkish: Istanbul B ...
Download / Learn more Package Citations See dependency  
msm  
Multi-State Markov and Hidden Markov Models in Continuous Time
Functions for fitting continuous-time Markov and hidden Markov multi-state models to longitudinal d ...
Download / Learn more Package Citations See dependency  
crossurr  
Cross-Fitting for Doubly Robust Evaluation of High-Dimensional Surrogate Markers
Doubly robust methods for evaluating surrogate markers as outlined in: Agniel D, Hejblum BP, Thiebau ...
Download / Learn more Package Citations See dependency  
envirem  
Generation of ENVIREM Variables
Generation of bioclimatic rasters that are complementary to the typical 19 bioclim variables. ...
Download / Learn more Package Citations See dependency  

27,268

R Packages

233,548

Dependencies

72,590

Author Associations

27,205

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA