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Iscores: scoring imputations methods

Overview

Iscores is a package intended to provide a framework for scoring imputations methods. It implements the scores described in Michel, Naef, Spohn and Meinshausen. 2021 . Examples of use of the library are shown below.

Installation

The package should be (soon) available on CRAN, To install the package from github you can run

install.packages("devtools")
devtools::install_github("missValTeam/Iscores")

Examples:

n <- 20
X <- cbind(rnorm(n),rnorm(n))
X.NA <- X
X.NA[,1] <- ifelse(runif(n)<=0.2, NA, X[,1])

imputations <- list()

imputations[[1]] <- lapply(1:5, function(i) {
  X.loc <- X.NA
  X.loc[is.na(X.NA[,1]),1] <- mean(X.NA[,1],na.rm=TRUE)
  return(X.loc)
})

imputations[[2]] <- lapply(1:5, function(i) {
  X.loc <- X.NA
  X.loc[is.na(X.NA[,1]),1] <- sample(X.NA[!is.na(X.NA[,1]),1], size = sum(is.na(X.NA[,1])), replace = TRUE)
  return(X.loc)
})

methods <- c("mean","sample")

Iscores(imputations = imputations, methods = methods, X.NA = X.NA)

Issues

To report an issue, please use the issue tracker on github.com.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.