miceFast
Fast Imputations Using 'Rcpp' and 'Armadillo'
Fast imputations under the object-oriented programming paradigm. Moreover there are offered a few functions built to work with popular R packages such as 'data.table' or 'dplyr'. The biggest improvement in time performance can be achieved for a calculation where a grouping variable is used. A single evaluation of a quantitative model for the multiple imputations is another major enhancement. A new major improvement is one of the fastest predictive mean matching in the R world because of presorting and binary search.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.9.1 |
rolling linux/jammy R-4.5 | miceFast_0.9.1.tar.gz |
1.1 MiB |
0.9.1 |
rolling linux/noble R-4.5 | miceFast_0.9.1.tar.gz |
1.1 MiB |
0.9.1 |
rolling source/ R- | miceFast_0.9.1.tar.gz |
891.1 KiB |
0.9.1 |
latest linux/jammy R-4.5 | miceFast_0.9.1.tar.gz |
1.1 MiB |
0.9.1 |
latest linux/noble R-4.5 | miceFast_0.9.1.tar.gz |
1.1 MiB |
0.9.1 |
latest source/ R- | miceFast_0.9.1.tar.gz |
891.1 KiB |
0.9.1 |
2026-04-26 source/ R- | miceFast_0.9.1.tar.gz |
891.1 KiB |
0.9.1 |
2026-04-23 source/ R- | miceFast_0.9.1.tar.gz |
891.1 KiB |
0.9.1 |
2026-04-09 windows/windows R-4.5 | miceFast_0.9.1.zip |
1.5 MiB |
0.8.5 |
2025-04-20 source/ R- | miceFast_0.8.5.tar.gz |
403.0 KiB |