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-4.5-noble)ccda_1.1.1.tar.gz(r-4.4-noble)
ccda_1.1.1.tgz(r-4.4-emscripten)ccda_1.1.1.tgz(r-4.3-emscripten)
ccda.pdf |ccda.html✨
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 5 years agofrom:9b49f07194. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 02 2024 |
| R-4.5-linux | OK | Dec 02 2024 |
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 |