# Fast Imputations Using 'Rcpp' and 'Armadillo'

## Documentation for package ‘miceFast’ version 0.9.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

miceFast-package | miceFast package for fast multiple imputations.
air_miss | airquality dataset with additional variables
compare_imp | Comparing imputations and original data distributions
corrData | Class '"Rcpp_corrData"'
fill_NA | 'fill_NA' function for the imputations purpose.
fill_NA.data.frame | 'fill_NA' function for the imputations purpose.
fill_NA.data.table | 'fill_NA' function for the imputations purpose.
fill_NA.matrix | 'fill_NA' function for the imputations purpose.
fill_NA_N | 'fill_NA_N' function for the multiple imputations purpose
fill_NA_N.data.frame | 'fill_NA_N' function for the multiple imputations purpose
fill_NA_N.data.table | 'fill_NA_N' function for the multiple imputations purpose
fill_NA_N.matrix | 'fill_NA_N' function for the multiple imputations purpose
miceFast | Class '"Rcpp_miceFast"'
naive_fill_NA | 'naive_fill_NA' function for the simple and automatic imputation
naive_fill_NA.data.frame | 'naive_fill_NA' function for the simple and automatic imputation
naive_fill_NA.data.table | 'naive_fill_NA' function for the simple and automatic imputation
naive_fill_NA.matrix | 'naive_fill_NA' function for the simple and automatic imputation
neibo | Finding in random manner one of the k closest points in a certain vector for each value in a second vector
pool | Pool results from models fitted on multiply imputed datasets
print.miceFast_pool | Print method for pooled MI results
Rcpp_corrData-class | Class '"Rcpp_corrData"'
Rcpp_miceFast-class | Class '"Rcpp_miceFast"'
summary.miceFast_pool | Summary method for pooled MI results
upset_NA | upset plot for NA values
VIF | 'VIF' function for assessing VIF.
VIF.data.frame | 'VIF' function for assessing VIF.
VIF.data.table | 'VIF' function for assessing VIF.
VIF.matrix | 'VIF' function for assessing VIF.