Package: stuart 0.10.2
stuart: Subtests Using Algorithmic Rummaging Techniques
Construct subtests from a pool of items by using ant-colony-optimization, genetic algorithms, brute force, or random sampling. Schultze (2017) <doi:10.17169/refubium-622>.
Authors:
stuart_0.10.2.tar.gz
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stuart_0.10.2.tgz(r-4.4-any)stuart_0.10.2.tgz(r-4.3-any)
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stuart.pdf |stuart.html✨
stuart/json (API)
# Install 'stuart' in R: |
install.packages('stuart', repos = c('https://martscht.r-universe.dev', 'https://cloud.r-project.org')) |
- fairplayer - MTMM fairplayer Intervention Data
- sia - Data from a German Meaning of Work Scale.
- sups - Data from a scale for Supervisor Support
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:d26db14d6c. Checks:OK: 3 NOTE: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 01 2024 |
R-4.5-win | OK | Nov 01 2024 |
R-4.5-linux | OK | Nov 01 2024 |
R-4.4-win | NOTE | Nov 01 2024 |
R-4.4-mac | NOTE | Nov 01 2024 |
R-4.3-win | NOTE | Nov 01 2024 |
R-4.3-mac | NOTE | Nov 01 2024 |
Exports:as.stuartFixedObjectivebruteforcecombinationscrossvalidateempiricalobjectivefixedobjectivegeneheuristicsholdoutkfoldmmasobjectivematricesrandomsamples
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
---|---|
STUART: Subtests Using Algorithmic Rummaging Techniques | stuart-package stuart |
Convert empirical to fixed objective. | as.stuartFixedObjective |
Subtest construction using a brute-force approach | bruteforce |
Compute the number of possible subtest combinations | combinations |
Cross-Validate a Measurement Model | crossvalidate |
Generate an empirical objective function for item selection. | empiricalobjective |
MTMM fairplayer Intervention Data (2009) | fairplayer |
Generate a fixed objective function for item selection. | fixedobjective |
Subtest construction using a simple genetic algorithm | gene |
Generating heuristics for the use in STUART subtest construction | heuristics |
Data selection for holdout validation. | holdout |
k-Folds Crossvalidation | kfold |
Subtest construction using the Max-Min-Ant-System | mmas |
Generate matrix-components for objective functions. | objectivematrices |
Generating random samples of Subtests | randomsamples |
Data from a German Meaning of Work Scale. | sia |
Data from a scale for Supervisor Support | sups |