The gap statistic approach is extended to estimate the number of clusters for categorical response format data. This approach and accompanying software is designed to be used with the output of any clustering algorithm and with distances specifically designed for categorical (i.e. multiple choice) or ordinal survey response data.
| Version: |
1.0.0 |
| Depends: |
R (≥ 4.2.0) |
| Imports: |
cultevo, magrittr, utils, ggplot2, pheatmap, dplyr, Polychrome, RColorBrewer, reshape2, tidyr, ComplexHeatmap, cluster, stats |
| Suggests: |
kableExtra, knitr, rmarkdown, testthat |
| Published: |
2024-12-09 |
| DOI: |
10.32614/CRAN.package.DiscreteGapStatistic |
| Author: |
Jeffrey Miecznikowski [aut],
Eduardo Cortes 
[aut, cre] |
| Maintainer: |
Eduardo Cortes <ecortesg at buffalo.edu> |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/ecortesgomez/DiscreteGapStatistic |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
DiscreteGapStatistic results |