mlim.summarize: mlim imputation summary

In mlim: Single and Multiple Imputation with Automated Machine Learning

mlim imputation summary

Description

provides information about estimated accuracy of the imputation as well as the overall procedure of the imputation.

Usage

mlim.summarize(data)

Arguments

data	dataset imputed with mlim

Value

estimated imputation accuracy via cross-valdiation procedure

Author(s)

E. F. Haghish

Examples

## Not run: 
data(iris)

# add 10% stratified missing values to one factor variable
irisNA <- iris
irisNA$Species <- mlim.na(irisNA$Species, p = 0.1, stratify = TRUE, seed = 2022)

# run the ELNET single imputation (fastest imputation via 'mlim')
MLIM <- mlim(irisNA)

# in single imputation, you can estimate the imputation accuracy via cross validation RMSE
mlim.summarize(MLIM)

## End(Not run)

mlim documentation built on Dec. 28, 2022, 2:33 a.m.