Package: rMOST 1.0.1
rMOST: Estimates Pareto-Optimal Solution for Hiring with 3 Objectives
Estimates Pareto-optimal solution for personnel selection with 3 objectives using Normal Boundary Intersection (NBI) algorithm introduced by Das and Dennis (1998) <doi:10.1137/S1052623496307510>. Takes predictor intercorrelations and predictor-objective relations as input and generates a series of solutions containing predictor weights as output. Accepts between 3 and 10 selection predictors. Maximum 2 objectives could be adverse impact objectives. Partially modeled after De Corte (2006) TROFSS Fortran program <https://users.ugent.be/~wdecorte/trofss.pdf> and updated from 'ParetoR' package described in Song et al. (2017) <doi:10.1037/apl0000240>. For details, see Study 3 of Zhang et al. (2023).
Authors:
rMOST_1.0.1.tar.gz
rMOST_1.0.1.zip(r-4.5)rMOST_1.0.1.zip(r-4.4)rMOST_1.0.1.zip(r-4.3)
rMOST_1.0.1.tgz(r-4.4-any)rMOST_1.0.1.tgz(r-4.3-any)
rMOST_1.0.1.tar.gz(r-4.5-noble)rMOST_1.0.1.tar.gz(r-4.4-noble)
rMOST_1.0.1.tgz(r-4.4-emscripten)rMOST_1.0.1.tgz(r-4.3-emscripten)
rMOST.pdf |rMOST.html✨
rMOST/json (API)
NEWS
| # Install 'rMOST' in R: |
| install.packages('rMOST', repos = c('https://diversity-paretooptimal.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 1 years agofrom:7c4eb385d9. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 03 2024 |
| R-4.5-win | OK | Nov 03 2024 |
| R-4.5-linux | OK | Nov 03 2024 |
| R-4.4-win | OK | Nov 03 2024 |
| R-4.4-mac | OK | Nov 03 2024 |
| R-4.3-win | OK | Nov 03 2024 |
| R-4.3-mac | OK | Nov 03 2024 |
Exports:MOSTParetoR_1C_2AIRParetoR_2CParetoR_2C_1AIRParetoR_3C
Dependencies:nloptr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| MOST | MOST |
| ParetoR_1C_2AIR | ParetoR_1C_2AIR |
| ParetoR_2C | ParetoR_2C |
| ParetoR_2C_1AIR | ParetoR_2C_1AIR |
| ParetoR_3C | ParetoR_3C |
