miceRanger

Description

Multiple Imputation has been shown to be a flexible method to impute missing values by Van Buuren (2007) <doi:10.1177/0962280206074463>. Expanding on this, random forests have been shown to be an accurate model by Stekhoven and Buhlmann <arXiv:1105.0828> to impute missing values in datasets. They have the added benefits of returning out of bag error and variable importance estimates, as well as being simple to run in parallel.

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Maintainer: ‘Sam Wilson <samwilson303@gmail.com>’

The Description field contains
  model by Stekhoven and Buhlmann <arXiv:1105.0828> to impute missing
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

Maintainer: ‘Sam Wilson <samwilson303@gmail.com>’

The Description field contains
  model by Stekhoven and Buhlmann <arXiv:1105.0828> to impute missing
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

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Maintainer: ‘Sam Wilson <samwilson303@gmail.com>’

The Description field contains
  model by Stekhoven and Buhlmann <arXiv:1105.0828> to impute missing
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

Maintainer: ‘Sam Wilson <samwilson303@gmail.com>’

The Description field contains
  model by Stekhoven and Buhlmann <arXiv:1105.0828> to impute missing
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

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