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Variance-aware Michaelis-Menten estimation, model screening, grouped enzyme-kinetic analyses, and clustered repeated-measurement workflows. The package implements profile-score estimators under working variance functions, together with a lightweight cluster-aware working-covariance extension, Wald and bootstrap confidence intervals, prediction utilities, and simulation helpers. Related methodology is discussed by Kim and Ma (2012) <doi:10.1007/s10463-011-0332-y>, Kim (2023) <doi:10.1002/sta4.606>, and Ma and Genton (2010) <doi:10.1111/j.1467-9868.2010.00741.x>.
| Version: | 0.0.2 |
| Depends: | R (≥ 4.1.0) |
| Imports: | graphics, grDevices, stats |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: | 2026-05-27 |
| DOI: | 10.32614/CRAN.package.inferMM |
| Author: | Mijeong Kim [aut, cre], Minkyoung Cha [aut], Ah Young Jeong [aut] |
| Maintainer: | Mijeong Kim <m.kim at ewha.ac.kr> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Citation: | inferMM citation info |
| Materials: | README, NEWS |
| CRAN checks: | inferMM results |
| Reference manual: | inferMM.html , inferMM.pdf |
| Vignettes: |
A Workflow for Variance-Aware Michaelis-Menten Analysis (source, R code) |
| Package source: | inferMM_0.0.2.tar.gz |
| Windows binaries: | r-devel: inferMM_0.0.2.zip, r-release: inferMM_0.0.2.zip, r-oldrel: inferMM_0.0.2.zip |
| macOS binaries: | r-release (arm64): inferMM_0.0.2.tgz, r-oldrel (arm64): inferMM_0.0.2.tgz, r-release (x86_64): inferMM_0.0.2.tgz, r-oldrel (x86_64): inferMM_0.0.2.tgz |
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