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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).

Versions across snapshots

VersionRepositoryFileSize
1.0.1 rolling linux/jammy R-4.5 rMOST_1.0.1.tar.gz 188.4 KiB
1.0.1 rolling linux/noble R-4.5 rMOST_1.0.1.tar.gz 188.9 KiB
1.0.1 rolling source/ R- rMOST_1.0.1.tar.gz 40.5 KiB
1.0.1 latest linux/jammy R-4.5 rMOST_1.0.1.tar.gz 188.4 KiB
1.0.1 latest linux/noble R-4.5 rMOST_1.0.1.tar.gz 188.9 KiB
1.0.1 latest source/ R- rMOST_1.0.1.tar.gz 40.5 KiB
1.0.1 2026-04-26 source/ R- rMOST_1.0.1.tar.gz 40.5 KiB
1.0.1 2026-04-23 source/ R- rMOST_1.0.1.tar.gz 40.5 KiB
1.0.1 2026-04-09 windows/windows R-4.5 rMOST_1.0.1.zip 194.1 KiB
1.0.1 2025-04-20 source/ R- rMOST_1.0.1.tar.gz 40.5 KiB

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