Package: optimus 0.2.0

optimus: Model Based Diagnostics for Multivariate Cluster Analysis

Assessment and diagnostics for comparing competing clustering solutions, using predictive models. The main intended use is for comparing clustering/classification solutions of ecological data (e.g. presence/absence, counts, ordinal scores) to 1) find an optimal partitioning solution, 2) identify characteristic species and 3) refine a classification by merging clusters that increase predictive performance. However, in a more general sense, this package can do the above for any set of clustering solutions for i observations of j variables.

Authors:Mitchell Lyons [aut, cre]

optimus_0.2.0.tar.gz
optimus_0.2.0.zip(r-4.5)optimus_0.2.0.zip(r-4.4)optimus_0.2.0.zip(r-4.3)
optimus_0.2.0.tgz(r-4.5-any)optimus_0.2.0.tgz(r-4.4-any)optimus_0.2.0.tgz(r-4.3-any)
optimus_0.2.0.tar.gz(r-4.5-noble)optimus_0.2.0.tar.gz(r-4.4-noble)
optimus_0.2.0.tgz(r-4.4-emscripten)optimus_0.2.0.tgz(r-4.3-emscripten)
optimus.pdf |optimus.html
optimus/json (API)
NEWS

# Install 'optimus' in R:
install.packages('optimus', repos = c('https://mitchest.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mitchest/optimus/issues

Datasets:
  • swamps - Dharawal National Park Upland Heath Swamps Plot Network

On CRAN:

Conda:

3.78 score 1 stars 12 scripts 171 downloads 3 exports 12 dependencies

Last updated 7 years agofrom:8caa20da60. Checks:1 OK, 8 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 07 2025
R-4.5-winNOTEMar 07 2025
R-4.5-macNOTEMar 07 2025
R-4.5-linuxNOTEMar 07 2025
R-4.4-winNOTEMar 07 2025
R-4.4-macNOTEMar 07 2025
R-4.4-linuxNOTEMar 07 2025
R-4.3-winNOTEMar 07 2025
R-4.3-macNOTEMar 07 2025

Exports:find_optimalget_characteristicmerge_clusters

Dependencies:latticeMASSMatrixmvabundnlmenumDerivordinalRcppRcppGSLstatmodtweedieucminf

Optimus workflow

Rendered fromoptimus-workflow.Rmdusingknitr::rmarkdownon Mar 07 2025.

Last update: 2017-03-23
Started: 2017-03-23