Package: mimdo 0.1.0
Geovert John Labita
mimdo: Multivariate Imputation by Mahalanobis Distance Optimization
Imputes missing values of an incomplete data matrix by minimizing the Mahalanobis distance of each sample from the overall mean [Labita, GJ.D. and Tubo, B.F. (2024) <doi:10.24412/1932-2321-2024-278-115-123>].
Authors:
mimdo_0.1.0.tar.gz
mimdo_0.1.0.tar.gz(r-4.5-noble)mimdo_0.1.0.tar.gz(r-4.4-noble)
mimdo_0.1.0.tgz(r-4.4-emscripten)mimdo_0.1.0.tgz(r-4.3-emscripten)
mimdo.pdf |mimdo.html✨
mimdo/json (API)
| # Install 'mimdo' in R: |
| install.packages('mimdo', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:1db2c746b7. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 21 2024 |
| R-4.5-linux | OK | Aug 21 2024 |
Exports:mimdo
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Multivariate Imputation by Mahalanobis Distance Optimization | mimdo |
