Variance-Aware Michaelis-Menten Estimation and Inference R package inferMM version 0.0.3 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>. Software Depends: R (>= 4.1.0) Imports: graphics, grDevices, stats Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Mijeong Kim <m.kim@ewha.ac.kr> Comprehensive R Archive Network (CRAN) Mijeong Kim [aut, cre], Minkyoung Cha [aut], Ah Young Jeong [aut] GPL-3 2026-06-04 application/tgz https://CRAN.R-project.org/package=inferMM doi:10.32614/CRAN.package.inferMM