Package:
miceDRF
Authors:
Krystyna Grzesiak, Jeffrey Näf
Category:
Multiple Imputation, MICE
Use-Cases:
Imputation, Distributional Random Forest
Popularity:
soon on CRAN
Description:
This package contains miceDRF imputation method and tools for measuring imputation performance.
Algorithms:
impute_mice_drf(): mice + Distributional Random Forest imputation
Datasets:
none
Further Information:
- Package repository: https://github.com/KrystynaGrzesiak.
Input:
data.frame, matrix
Example:
library(miceDRF)
library(mice)
n <- 200
d <- 5
X <- matrix(runif(n * d), nrow = n, ncol = d)
pmiss <- 0.2
X.NA <- apply(X, 2, function(x) {
U <- runif(length(x))
ifelse(U <= pmiss, rep(NA, length(x)), x)
})
imp <- mice(X.NA, m = 1, method = "DRF")
Ximp <- mice::complete(imp)