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This function performs imputation using MICE and Distributional Random Forest

Usage

mice.impute.DRF(
  y,
  ry,
  x,
  wy = NULL,
  min.node.size = 1,
  num.features = 10,
  num.trees = 10,
  ...
)

Arguments

y

words, words...

ry

words, words...

x

words, words...

wy

words, words...

min.node.size

words, words...

num.features

words, words...

num.trees

words, words...

References

This method is described in detail in:

Näf, J., Scornet, E., & Josse, J. (2024). What is a good imputation under MAR missingness?. arXiv. https://arxiv.org/abs/2403.19196

It's based on:

Cevid, D., Michel, L., Näf, J., Meinshausen, N., and B¨ uhlmann, P. (2022). Distributional random forests: Heterogeneity adjustment and multivariate distributional regression. Journal of Machine Learning Research, 23(333):1–79.