Nothing
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).
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Chelsea Song [aut, cre] (<https://orcid.org/0000-0003-0910-1281>), Yesuel Kim [ctb] (<https://orcid.org/0000-0002-8486-7693>) |
| Maintainer | Chelsea Song <qianqisong@gmail.com> |
| License | MIT + file LICENSE |
| Version | 1.0.1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the rMOST package in your browser
Any scripts or data that you put into this service are public.
