Package: ccda 1.1.1
Solt Kovacs
ccda: Combined Cluster and Discriminant Analysis
Implements the combined cluster and discriminant analysis method for finding homogeneous groups of data with known origin as described in Kovacs et. al (2014): Classification into homogeneous groups using combined cluster and discriminant analysis (CCDA). Environmental Modelling & Software. <doi:10.1016/j.envsoft.2014.01.010>.
Authors:
ccda_1.1.1.tar.gz
ccda_1.1.1.tar.gz(r-4.7-any)ccda_1.1.1.tar.gz(r-4.6-any)
ccda_1.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
ccda/json (API)
| # Install 'ccda' in R: |
| install.packages('ccda', repos = c('https://cran.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 from:9b49f07194. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 99 | ||
| source / vignettes | OK | 138 | ||
| linux-release-x86_64 | OK | 99 | ||
| wasm-release | OK | 95 |
Exports:ccda.mainpercentageplotccda.clusterplotccda.q95plotccda.results
Dependencies:MASS
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Combined Cluster and Discriminant Analysis | ccda.main |
| Calculation of the ratio of correctly classified cases by linear discriminant analysis | percentage |
| Plot of the basic grouping | plotccda.cluster |
| CCDA density drawer | plotccda.q95 |
| Plot of the results of ccda.main | plotccda.results |