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missForest

missForest is a nonparametric, mixed-type imputation method for basically any type of data.
Here, we host the R-package "missForest" for the statistical software R.

The method is based on the publication Stekhoven and Bühlmann, 2012. The R package contains a vignette on how to use "missForest" in R including many helpful examples. Upcoming innovations:

  • use of prediction
  • 'real' multiple imputation

Contact me by email: stekhoven@quantik.ch References: Stekhoven, D.J. and Buehlmann, P. (2012), 'MissForest - nonparametric missing value imputation for mixed-type data', Bioinformatics, 28(1) 2012, 112-118, doi: 10.1093/bioinformatics/btr597

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install.packages('missForest')

Monthly Downloads

9,436

Version

1.4

License

GPL (>= 2)

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Last Published

December 31st, 2013

Functions in missForest (1.4)

missForest-package

Nonparametric Missing Value Imputation using Random Forest
varClass

Extract Variable Types from a Dataframe
prodNA

Introduce Missing Values Completely at Random
mixError

Compute Imputation Error for Mixed-type Data
nrmse

Normalized Root Mean Squared Error
missForest

Nonparametric Missing Value Imputation using Random Forest