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r-missforest

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The function 'missForest' in this package is used to impute missing values particularly in the case of mixed-type data. It uses a random forest trained on the observed values of a data matrix to predict the missing values. It can be used to impute continuous and/or categorical data including complex interactions and non-linear relations. It yields an out-of-bag (OOB) imputation error estimate without the need of a test set or elaborate cross-validation. It can be run in parallel to save computation time.

Installation

To install this package, run one of the following:

Conda
$conda install conda-forge::r-missforest

Usage Tracking

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About

Summary

The function 'missForest' in this package is used to impute missing values particularly in the case of mixed-type data. It uses a random forest trained on the observed values of a data matrix to predict the missing values. It can be used to impute continuous and/or categorical data including complex interactions and non-linear relations. It yields an out-of-bag (OOB) imputation error estimate without the need of a test set or elaborate cross-validation. It can be run in parallel to save computation time.

Last Updated

Oct 26, 2025 at 15:48

License

GPL-2.0-or-later

Supported Platforms

noarch

Unsupported Platforms

linux-64 Last supported version: 1.4
macOS-64 Last supported version: 1.4
win-64 Last supported version: 1.4