Package: ordinalMIC 1.0.0

ordinalMIC: Minimum Inhibitory Concentration Estimation from Ordinal Regression Models

Provides tools to estimate minimum inhibitory concentration (MIC) and conduct rigorous pairwise comparisons (delta, fold‑change, and difference of difference tests) from cumulative‑link models fitted with 'ordinal::clm'.

Authors:Carson Stacy [aut, cre]

ordinalMIC_1.0.0.tar.gz
ordinalMIC_1.0.0.zip(r-4.7)ordinalMIC_1.0.0.zip(r-4.6)ordinalMIC_1.0.0.zip(r-4.5)
ordinalMIC_1.0.0.tgz(r-4.6-any)ordinalMIC_1.0.0.tgz(r-4.5-any)
ordinalMIC_1.0.0.tar.gz(r-4.7-any)ordinalMIC_1.0.0.tar.gz(r-4.6-any)
ordinalMIC_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
ordinalMIC/json (API)

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

Bug tracker:https://github.com/clstacy/ordinalmic/issues

Pkgdown/docs site:https://clstacy.github.io

Datasets:
  • yeast_df - Simulated Yeast Stress-Survival Data

On CRAN:

Conda:

2.60 score 4 scripts 2 exports 22 dependencies

Last updated from:6cfa30981e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK156
source / vignettesOK156
linux-release-x86_64OK166
macos-release-arm64OK203
macos-oldrel-arm64OK164
windows-develOK147
windows-releaseOK93
windows-oldrelOK76
wasm-releaseOK85

Exports:mic_solvetidy.mic_solve

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigR6RColorBrewerrlangS7scalestibbleutf8vctrsviridisLitewithr