RfEmpImp: Multiple Imputation using Chained Random Forests
An R package for methods of multiple imputation using chained
random forests. Implemented methods can handle missing data in mixed types
of by using prediction-based or node-based conditional distributions
constructed using random forests. For prediction-based imputation,
the method based on the empirical distribution of out-of-bag prediction
errors of random forests, and the method based on normality assumption are
provided for continuous variables. And the method based on predicted
probabilities is provided for categorical variables. For node-based
imputation, the method based on the conditional distribution formed by
the predicting nodes of random forests, and the method based on proximity
measures of random forests are provided. More details of the statistical
methods can be found in Hong et al. (2020) <arXiv:2004.14823>.
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