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-any)ordinalMIC_1.0.0.zip(r-4.6-any)ordinalMIC_1.0.0.zip(r-4.5-any)
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:

1.70 score 4 scripts 2 exports 22 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK147
source / vignettesOK368
linux-releaseOK111
macos-releaseOK116
macos-oldrelOK94
windows-develOK83
windows-releaseOK81
windows-oldrelOK100
wasm-releaseOK90

Exports:mic_solvetidy.mic_solve

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigR6RColorBrewerrlangS7scalestibbleutf8vctrsviridisLitewithr